WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Opportunity

At Zeta Global, identity is at the core of our marketing cloud. The Identity team builds and operates backend services that power the Zeta Identity Graph - collecting, resolving, and maintaining billions of behavioral, demographic, and transactional signals. These services enable people-based marketing at scale, ensure trust and transparency in how identity data is managed, and provide critical APIs and event streams consumed across Zeta’s platform. Our systems support more than 235 million consumer profiles and process billions of events monthly, requiring services that are highly available, low-latency, and built to scale

We are looking for a Lead Software Engineer who brings strength in both backend distributed systems and data engineering. In this role, you’ll design APIs and event-driven services, scale our systems to handle rapidly growing data volumes, and modernize our platform for resilience, transparency, and performance.

You Will:

• Design and build backend services and APIs for identity resolution, graph transparency, and integrations.
• Develop and optimize event-driven pipelines and workflows processing billions of signals.
• Deploy and operate cloud-native services on EKS/Kubernetes, leveraging Helm for repeatable deployments.
• Ensure reliability, observability, and scalability across services and data pipelines.
• Collaborate across engineering, product, and data teams to deliver end-to-end identity solutions.
• Mentor engineers and influence architecture and roadmap

You Have:

• 5+ years of experience in backend and/or data engineering at scale.
• Strong skills in Python, Java, or Scala, with expertise in APIs, distributed systems, and event-driven design.
• Hands-on experience with Kafka (or similar), Spark/Hive/Flink, and workflow schedulers (Airflow/Luigi).
• Proficiency with Kubernetes (EKS preferred) and deployment practices (Helm, service meshes).
• Solid knowledge of SQL, data modelling, and cloud platforms (AWS).
• Familiarity with columnar / NoSQL databases (Aerospike, Snowflake, HBase, Scylla, Couchbase).
• Strong communication skills and a track record of driving technical direction and mentoring teams.

Bonus Skills:

• Experience with large-scale or multi-tenant distributed systems.
• Exposure to real-time streaming frameworks (Flink, Storm).
• Knowledge of open table formats (Iceberg, Hudi, Delta Lake).
• Background in security, compliance, or privacy related to identity systems.

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $150,000 - $200,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-DD1

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Opportunity

At Zeta Global, identity is at the core of our marketing cloud. The Identity team builds and operates backend services that power the Zeta Identity Graph - collecting, resolving, and maintaining billions of behavioral, demographic, and transactional signals. These services enable people-based marketing at scale, ensure trust and transparency in how identity data is managed, and provide critical APIs and event streams consumed across Zeta’s platform. Our systems support more than 235 million consumer profiles and process billions of events monthly, requiring services that are highly available, low-latency, and built to scale

We are looking for a Lead Software Engineer who brings strength in both backend distributed systems and data engineering. In this role, you’ll design APIs and event-driven services, scale our systems to handle rapidly growing data volumes, and modernize our platform for resilience, transparency, and performance.

You Will:

• Design and build backend services and APIs for identity resolution, graph transparency, and integrations.
• Develop and optimize event-driven pipelines and workflows processing billions of signals.
• Deploy and operate cloud-native services on EKS/Kubernetes, leveraging Helm for repeatable deployments.
• Ensure reliability, observability, and scalability across services and data pipelines.
• Collaborate across engineering, product, and data teams to deliver end-to-end identity solutions.
• Mentor engineers and influence architecture and roadmap

You Have:

• 5+ years of experience in backend and/or data engineering at scale.
• Strong skills in Python, Java, or Scala, with expertise in APIs, distributed systems, and event-driven design.
• Hands-on experience with Kafka (or similar), Spark/Hive/Flink, and workflow schedulers (Airflow/Luigi).
• Proficiency with Kubernetes (EKS preferred) and deployment practices (Helm, service meshes).
• Solid knowledge of SQL, data modelling, and cloud platforms (AWS).
• Familiarity with columnar / NoSQL databases (Aerospike, Snowflake, HBase, Scylla, Couchbase).
• Strong communication skills and a track record of driving technical direction and mentoring teams.

Bonus Skills:

• Experience with large-scale or multi-tenant distributed systems.
• Exposure to real-time streaming frameworks (Flink, Storm).
• Knowledge of open table formats (Iceberg, Hudi, Delta Lake).
• Background in security, compliance, or privacy related to identity systems.

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $150,000 - $200,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-DD1

The Role

Join us in revolutionizing the financial landscape. SoFi is seeking enthusiastic Senior Software Engineers who are ready to lead the development of key advancement to the next generation of our financial services platform.

Data Trust org leads the path for building platform services, and governance initiatives — from integrating diverse data sources into governance tools to evolving the foundational architecture that supports SoFi’s long-term growth

Data Trust’s charter includes

• Development and management of the Unified Data Catalog and Discovery Tools
• Ownership and other metadata associated with the Catalog
• Lineage and retention policies
• Data Quality Strategy and Standardization (Tiered Ownership, SLOs)
• Enforce regulatory compliance and privacy across data
• Data Governance enforcement and tooling (Data Contracts, RBAC mechanisms).
• Building self-service tools for Data Owners and Data Engineers.

What You’ll Do

As an emerging leader within our team, you will focus on building out the backend services for our next-generation metadata architecture. This role involves full product lifecycle engagement, from initial concept to deployment.

Key responsibilities for this role include:

• Implementing new capabilities, ensuring code quality, and delivering highly-available, scalable services.
• Success requires close technical collaboration with Product, Marketing, Operations, Business, Legal, and Compliance teams. You will be responsible for translating business requirements from these stakeholders into effective technical solutions that provide outstanding value to our members.
• Leading the technical evolution of one or more key platform subsystems.
• Expertly leverage existing solution patterns and understand when to differentiate resulting in well-structured, maintainable code.
• Ability to understand data models, APIs, scaling concerns, and failure modes in order to make effective trade-offs between maintainability and performance.
• Creating stability by writing meaningful tests, considering observability, and leveraging your ability to debug complex issues across multiple system layers.
• The ability to create clear design and operational documentation.
• Contributes to code reviews, is a role model for more junior engineers, and contributes to team efficiency, beyond personal output.

What You’ll Need

• Bachelor's or Master's degree in Computer Science, or Software Engineering
• 3+ years as a professional, full-time Software Engineer, or similar relevant work experience.
• Proficient coding in Java, Kotlin, Python or other similar object-oriented programming language.
• Proficient working with GIT and related CI/CD systems.
• Experience with public cloud compute, storage, and infrastructure.
• Experience with any data warehousing solution like Snowflake and IAC tools to provision platform infrastructure.
• Experience with Kafka, Docker, Kubernetes, and Spring Boot or similar frameworks.
• Deep understanding of relational and document database fundamentals.
• Deep understanding of fundamental distributed systems concepts.

Nice To Have

• Full-Stack experience in both back-end (Kafka, Redis, Docker) and front-end (JavaScript, TypeScript, React).
• Experience with microservices design principles and architecture.
• Experience with workflow orchestration technology (AWS step function, Airflow, Temporal).
• Experience working with Data Platforms

We're driven to push boundaries and deliver exceptional products to help our members achieve financial stability. If you have the passion and a commitment to customer success, we want to hear from you.

About this role

The Account Manager, Fulfillment owns the post-onboarding relationship for a portfolio of brands enrolled in Fulfilled by Faire. This is a commercially-oriented role sitting at the intersection of customer success, strategic account management, and operational consulting. The AM is accountable for brand retention, unlocking addressable SKUs within FbF, and driving the consolidation of non-Faire wholesale volume onto the platform — ultimately increasing FbF's share of each brand's total distribution.

This role requires equal fluency in relationship management and data-driven storytelling. The best AM will translate operational metrics into commercial conversations, coach brands on the cost, ease, and growth benefits of FbF, and proactively identify at-risk accounts before churn signals become churn events.

What you’ll do 

1. Business Reviews & Brand Relationships

• Own the QBR/MBR cadence for your portfolio of brands — prepare, deliver, and follow up on structured business reviews that connect FbF operational health to brand revenue outcomes. Note: this is specific to Fulfillment, different than BSMs
  • BSM = general portfolio of programs and brand perf on Faire, how's it all going, ROI of each program etc.
  • Fulfillment AM = goal of retention + revenue; then how to coach brands on cost/ease/growth
• Build multi-threaded relationships within brand accounts (founder, ops lead, sales director) to ensure Faire has a durable presence beyond a single point of contact.
• Develop and maintain a living account plan for each brand documenting their wholesale strategy, growth goals, pain points, and consolidation opportunity.
• Track and surface brand health signals (fulfillment SLA trends, return rates, catalog coverage, order velocity) to shape the review narrative and prioritize interventions.

2. Churn Prevention & Retention

• Maintain a real-time risk register for your portfolio — flag brands showing signs of disengagement (declining order volume, SLA friction, support ticket escalation, low catalog activity) and activate retention protocols before churn is formally triggered.
• Lead escalation management for brands experiencing fulfillment issues; coordinate internally with FbF Ops and Warehouse teams to resolve and close the loop with the brand (including post onboarding questions + feedback)
• Build and recommend custom “save” plans for at-risk accounts, including fee concessions, operational audits, and executive engagement where warranted (ie where to offer appeasements and program benefits)
• Conduct structured off-boarding interviews with any brand that churns to capture root cause and feed insights back to product, ops, and leadership.

3. Consolidation & Non-Faire Wholesale Volume

• Map each brand's total wholesale footprint — identify the volume, channels, and retail segments currently fulfilled outside of Faire and quantify the consolidation opportunity.
• Build and present a compelling consolidation case tailored to each brand: cost per order comparison (FbF vs. 3PL vs. self-fulfill), SLA reliability benchmarks, and projected net margin impact of migrating volume to FbF.
• Develop milestone-based migration plans for brands willing to consolidate, coordinating with Warehouse Ops to ensure capacity and onboarding support.
• Track consolidation pipeline and report GMV-at-risk (volume outside Faire) alongside GMV-converted (volume successfully moved to FbF) in your portfolio metrics.

4. Catalog Penetration & Upsell

• Audit each brand's active Faire catalog against their full SKU assortment — identify categories, price points, or product lines with low representation on the platform.
• Partner with brands to expand catalog depth and breadth, with particular focus on high-velocity SKUs and seasonal assortment that can drive incremental retailer demand.
• Position catalog growth as a retention lever: more SKUs in FbF increases platform stickiness and makes brand consolidation structurally harder to reverse

Qualifications

• 3–5 years of experience in account management, customer success, or strategic partnerships — preferably in a marketplace, logistics, e-commerce, or B2B SaaS context.
• Demonstrated track record of owning commercial outcomes (retention, expansion revenue, or upsell) within a named account portfolio.
• Strong analytical fluency — able to pull and synthesize data from BI tools (Looker, Mode, Snowflake) to build business cases and executive-level narratives.
• Excellent written and verbal communication; comfortable presenting to brand founders and operators with conviction and clarity.
• Experience managing escalations and cross-functional coordination under time pressure.

Preferred

• Background in wholesale, retail supply chain, 3PL operations, or fulfillment — understanding of landed cost economics and operational trade-offs is a meaningful differentiator.
• Experience at a marketplace or platform company with both buyer and seller stakeholders.
• Familiarity with Zendesk, Salesforce, or similar CRM/support tooling.
• Comfort with ambiguity and iterative process-building; this role will help define its own playbook.

Salary Range

On-Target Earnings (OTE) Range
San Francisco: the pay range for this role is $132,000 to $181,500 per year.

This role will also be eligible for equity and benefits. Actual On-Target Earnings (OTE) will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The OTE range provided is subject to change and may be modified in the future.

About the Role

The Data Governance function is pivotal in ensuring the integrity, trustworthiness, and effective management of Chime’s data assets. Our mission is to establish and operationalize data governance frameworks that not only meet compliance requirements, but actively enable high-confidence decision making across the company.  As a Data Governance Engineer, you will develop and implement policies and tools for data quality, developer enablement, certified datasets, and governance automation - with a sharp focus on building trust signals and scorecards that help data consumers quickly understand and act on the reliability of Chime's data.

This is a hands-on engineering role. You will write production-quality code to build automation for governance and data quality processes using Terraform, Python (or similar languages), and contribute to internal libraries, frameworks, and orchestration workflows that enable scalable governance.

You will partner closely with data engineering, analytics, product engineering, and compliance teams to:

• Support Chime in data compliance and risk reduction initiatives
• Establish data quality as a product discipline
• Build trust signals and scorecards that make data reliability transparent and data context valuable for a variety of use cases
• Implement governance workflows upstream, where data are created
• Ensure data context and metadata are sufficient for downstream use cases, including AI applications

You will be involved in reviews of technical designs and implementation plans to provide guidance on appropriate development from a data governance and compliance perspective, acting as a trusted advisor to teams innovating at Chime. You will also be a strong advocate and leader for Artificial Intelligence tooling and adoption at Chime, bringing curiosity and a practical eye for where AI creates leverage in data governance workflows. This role is 40% strategic influence, 40% development and building, and 20% stakeholder management and support.

The base salary for this role and level of experience will begin at $160,000.00 and go up to $221,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Build Data Trust Infrastructure: Design and implement trust scorecards, trust signals, and quality indicators that give data consumers real-time visibility into data reliability - and partner with producers upstream to embed quality checks at the source before issues propagate downstream.
• Drive Data Quality Strategy: Own and evolve Chime's data quality strategy end-to-end. Design and partner with engineering teams to implement data quality frameworks and monitoring systems that proactively identify, surface, and resolve data issues at scale.
• Develop and Implement Data Governance Policies: Create and enforce policies for data classification, quality, and lifecycle management, ensuring data integrity and compliance with SOX and other applicable regulatory standards.
• Enable the Data Catalog: Collaborate on the development, adoption, and enrichment of Chime's data catalog - improving discoverability, context richness (lineage, ownership, definitions, usage guidance), and the overall experience of working with Chime's data.
• Automate Governance Processes: Develop and deploy automation solutions for data governance tasks, such as metadata management, data lineage tracking, access controls, and quality remediation workflows.
• Champion SOX Compliance: Play an active role in Chime's SOX compliance efforts, ensuring that data governance practices, controls, and audit trails meet regulatory requirements and are well-documented.
• Lead AI Adoption for Data Governance: Serve as a leader and advocate for AI tooling within the data governance space - identifying opportunities to apply AI to automate governance workflows, improve data context, enhance trust scoring, and accelerate adoption of governance best practices across engineering teams.
• Collaborate Across Teams: Work closely with data engineers, analysts, and compliance officers to align data governance initiatives with business needs and regulatory requirements.

To thrive in this role, you have

• Experience: 5+ years in data engineering, data governance, or a related field, with hands-on experience in data classification, cataloging, quality assurance, and trust frameworks. Engineering ability to design and implement data governance and quality processes is critical to success.
• Trust & Quality Expertise: Demonstrated experience building data trust signals, quality scorecards, or similar frameworks that make data reliability visible and actionable for both engineers and non-technical stakeholders.
• Programming Experience: Proficiency in Python or a comparable programming language, and experience building scalable data tooling or automation pipelines.
• Curiosity and Relentlessness: You are genuinely curious about data, technology, and the problems that sit at the intersection of the two. You don't let ambiguity stop you - you dig in, ask the right questions, and keep pushing until you've found the right answer or built the right solution. You bring energy and persistence to hard problems and don't need external pressure to drive yourself forward.
• Composure in Complexity: Data governance at a fintech means navigating competing priorities, regulatory constraints, sprawling data ecosystems, and stakeholders with different mental models of "good." You thrive in this environment rather than shrinking from it - you can hold complexity without getting overwhelmed, break it into manageable pieces, and make steady progress without waiting for perfect conditions.
• Exceptional Communication: You are a terrific communicator in both verbal and written form. You can write a crisp one-pager that earns buy-in from a skeptical audience, run a meeting that ends with clarity instead of confusion, and translate deeply technical concepts into plain language that moves people to action. You treat communication as a core part of the job, not an afterthought.
• Product Management Mindset: You think like a product manager as much as an engineer. You ask "who is this for and what problem does it solve?" before writing a line of code. You prioritize ruthlessly, define success before you start building, and care about adoption and outcomes - not just delivery. You treat your internal stakeholders as customers and design solutions with their experience in mind.
• AI Curiosity and Advocacy: Genuine curiosity about AI and its applications in the data governance space, with an appetite for identifying and piloting new tools and workflows that improve the experience of working with Chime's data.
• Technical Proficiency: Strong knowledge of data governance tools and platforms, and experience with cloud data warehouses like Snowflake. Experience with data catalog platforms and driving adoption across engineering organizations is a strong plus.
• Bonus: Compliance Knowledge: Familiarity with SOX, CCPA, and other data privacy and financial regulations, and ability to apply technical skills to governance practices that meet audit and compliance requirements.

#LI-Onsite #LI-GC1

About the Role

The Data engineering team has been created keeping in mind the importance and criticality of data for the overall success of Chime.  The mission of this group is to build scalable data artifacts and insights that enable accurate, governed, data-driven decision-making.. As a core member of the team, you will have the opportunity to build scalable data pipelines and frameworks.  Additionally, you will have the unique opportunity to architect and build workflows that could potentially become de facto standards for the fintech industry.

The base salary offered for this role and level of experience will begin at $164,000.00 and go up to $227,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Be a hands-on data engineer, building, scaling and optimizing ETL pipelines
• Design data schemas and scale them data  for 10x data growth 
• Ownership of all aspects of data - data quality, data governance, schema design, data quality and security
• Develop scalable data architecture and standardized data models that enable self-serve data insights using AI.
• Own the ETL workflows and make sure the pipeline meets data quality and availability requirements
• Work closely with partner teams, like Data Science, Analytics and DevOps

To thrive in this role, you have

• 5+ years experience transforming data to governed and lucid datasets
• 5+ years of hands-on experience to build and deploy production-quality data pipelines
• 5+ years of experience working with stakeholders to provide business insights
• 5+ years of experience writing SQL, Spark, AWS Glue, EMR, Airflow, Python 
• 3+ years of hands-on experience using any MPP database system like Snowflake, AWS Redshift or Teradata
• Track record of successful partnerships with Analytics, Data Science and DevOps teams 
• Understanding of key metrics for data pipelines and has built solutions to provide visibility to partner teams
• Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary.

#LI-Onsite #LI-GC1

About the Role

The Senior Processor Implementation Manager is a senior individual contributor role within ChimeCore’s Processor Operations function, focused on ensuring the reliable implementation, validation, and operational readiness of payment processors, funds flows, and platform changes across ChimeCore. This role exists to apply deep system knowledge, operational judgment, and data expertise to complex payment workflows while partnering closely with Engineering, Accounting, Finance and Banks Operations teams. Success in this role is defined by high-quality implementations, faster issue resolution, and strong cross-functional trust.

The base salary offered for this role and level of experience will begin at $156,000 and up to $215,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role you can expect to

• Lead complex processor implementations, migrations, and platform changes within defined Processor Operations scope, ensuring operational readiness and clear handoff to steady-state owners.
• Serve as a subject matter expert on ChimeCore payment flows, transaction lifecycles, and data models across multiple payment rails.
• Partner with Engineering to review changes, validate operational assumptions, and surface downstream impacts, running it by leadership where approval authority is required.
• Support Accounting, Audit, Risk, and Finance by interpreting platform behavior and transaction data to aid investigations and reporting
• Participate in incident response and escalations by driving investigation, proposing hypotheses, and supporting remediation, with accountability shared across owning teams.
• Define expected versus anomalous processor behavior and contribute to the design of monitors and alerts in partnership with Engineering and Processor Operations.
• Perform advanced data analysis and SQL-based investigations to support reconciliation research root-cause analysis and be able to articulate the finding to a broader audience. Produce clear documentation of processor behavior, funds flows, and operational nuances to reduce dependency on individual knowledge.
• Act as a trusted advisor to Implementation and Reconciliation Managers, providing implementation context and guidance while avoiding single-threaded dependency.

To thrive in this role, you have

• 8+ years in bank and/or payment operations with a broad understanding of operations; including accounting, funds flow, settlement, processing, etc. 
• A strong reconciliation background
• An understanding of the end-to-end payments ecosystem, including payment methods, card networks, issuer processing, and the regulatory environment
• An understanding of ACH originations, returns, settlements and everything in between, AAP certification is a huge plus
• Familiarity with network operations including Visa, Mastercard, PLUS, and Star, as well as with network vendors that facilitate AFT/OCT payments and other forms of card-based money movement
• Extensive experience with Google Office (Sheets, Docs and Slides), analytics platforms (Looker, Snowflake), SQL, core banking systems and related products.
• Experience working cross functionally with Product, Accounting, Compliance, Legal, Risk & Engineering to identify, evaluate and size opportunities and prioritize work
• Experience driving continuous improvement projects, where you’ve applied deep knowledge to uncover and execute both short term and long term optimizations
• A member obsessed mindset, eager to learn and improve the user experience
• A curious and creative problem solving ability - can facilitate resolution of issues in a timely manner by working cross-functionally with product and engineering teams
• Excellent business acumen, communication skills and a self-starting attitude

#LI-Onsite #LI-GC1

About the role

We’re seeking a Finance Associate to support the Payments function at Chime! In this role, you will play a critical part in ensuring forecasting accuracy while driving forward high-impact strategic and financial initiatives. You’ll partner closely with business leaders and finance team members to provide insights, influence decision-making, and help shape Chime’s financial strategy.

Supporting Cost of Revenue (COR), you will collaborate with cross-functional partners across Strategy, Product, Data, Engineering, and Accounting to drive accuracy, visibility, and predictability in our cost forecasting. You will help design and operationalize scalable forecasting models, improve data pipelines, and ensure alignment between financial models and underlying business drivers.

You will support key COR forecasting areas such as processing, network, and bank-related costs, partnering with stakeholders to understand key drivers like transaction volume, pricing changes, and product evolution. You will also work closely with Accounting during close to validate actuals, explain variances, and ensure financial accuracy.

In addition, you’ll play a key role in the bottoms-up planning and forecasting process,  develop financial models and reporting, and proactively identify opportunities to leverage AI and automation to improve forecasting accuracy, scalability, and efficiency. We are looking for an analytical problem-solver who can break down complex problems into actionable components without losing sight of the overall strategy.

The base salary offered for this role and level of experience will begin at $105,000.00 and up to $145,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Own and improve COR forecasting processes, incorporating key drivers such as transaction volumes, pricing, vendor changes, and product evolution
• Develop, deliver, and maintain Cost of Revenue reporting and dashboards (e.g., vendor costs, transaction drivers) to ensure visibility and accuracy for business and finance leadership
• Partner cross-functionally with Strategy, Product, Data, Engineering, and Accounting to support financial decision-making and accountability
• Support monthly close processes by validating actuals, and explaining variances and business performance across COR categories
• Leverage AI and automation to streamline financial processes, improve data quality, and enhance scalable reporting and forecasting capabilities that support Chime’s growth and enable smarter, faster decision-making
• Support ad hoc analyses and strategic initiatives focused on optimization opportunities across COR

To thrive in this role, you have

• Minimum 3+ years of Finance/FP&A, investment banking, Big 4 accounting/advisory, or consulting experience
• Bachelor's Degree, or equivalent degree in Finance, Accounting, Economics or other relevant field
• Track record of budgeting, forecasting, and financial modeling with strong accuracy and attention to detail
• Strong sense of ownership and commitment to quality, working diligently to navigate ambiguity/obstacles and drive projects to completion
• Strong process-improvement mindset with demonstrated ability to leverage AI and automation to scale finance workflows and improve forecasting precision and turnaround time
• Proven ability to manage multiple priorities and competing deadlines in a fast-paced environment
• Advanced G-Suite, Microsoft Excel, Word, and presentation tools (PowerPoint, G-Slides) skills required
• Experience identifying, designing, or deploying AI-driven use cases within finance workflows (e.g., forecasting automation, reporting acceleration, variance analysis, or scenario modeling)
• Bonus Experience: Pigment, Netsuite, Looker, Workday, SQL, Snowflake, Python/coding tools, and direct experience with R&D and/or transaction loss forecasting

#LI-BE1 #LI-Onsite

About the Role

Together AI is building high-performance AI inference infrastructure and the software platform around it. We're looking for a senior Analytics Engineer who sits at the intersection of data engineering and business intelligence — someone who can turn raw, complex data into clean, trusted, well-documented models that the whole company can reason from.

You'll own the transformation layer of our data warehouse: shaping bronze/silver/gold models, designing dimensional schemas, and acting as the connective tissue between engineering systems and business stakeholders. You are equally comfortable deep in a dbt project and in a room with Finance, GTM, and Product aligning on definitions.

Requirements

• Expert SQL: window functions, complex aggregations, query optimization, cost-aware pattern selection, proficiency in Snowflake or equivalent cloud warehouse.
• dbt: deep, production-grade experience — models, tests (singular + generic), docs, snapshots, macros, packages, and incremental strategies. You've designed a dbt project from scratch and maintained it in production.
• Airflow / Astronomer: production DAG authoring, backfill handling, reliability patterns, and the Cosmos dbt integration.
• Dimensional modeling: you've read Kimball (or absorbed the equivalent), know the difference between star and snowflake schemas by feel, understand slowly changing dimensions, and can explain why a fact table's grain matters.
• Stakeholder management: demonstrated experience partnering with non-technical stakeholders, driving metric alignment, and delivering trusted data products — not just pipelines.
• Strong written communication: your documentation and async updates are clear enough that people don't need to ask follow-up questions.

Strong plus

• Experience with financial data or billing data — ARR, usage-based billing, invoice reconciliation, revenue recognition patterns. We operate a usage-based inference billing system and this context transfers directly.
• Experience with PII handling, data masking, access-tier modeling, or compliance work (SOC 2, ISO 27001, GDPR, CCPA).
• Familiarity with lakehouse patterns (Iceberg, Delta, Hudi) and hybrid warehouse/lake architectures.
• Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.
• Experience with Hex, Metabase, or similar notebook/BI tooling that sits on top of your dbt models.
• Prior experience in a high-growth AI/ML infrastructure or platform company.

Responsibilities

Modeling & transformation

• Own and evolve the dbt transformation layer: design, implement, test, document, and maintain modular dbt projects that cover billing, product usage, financial data, and operational metrics.
• Build analytics-ready dimensional models following Kimball methodology: star schemas, conformed dimensions, fact tables with the right grain, and SCD Type 2 for slowly changing entities.
• Design for correctness, performance, and cost — partition strategies, incremental models, and avoiding full-table scans.
• Build and maintain a semantic/metrics layer with consistent, auditable metric definitions reused across notebooks, BI, and APIs.

Pipeline orchestration

• Author and maintain Airflow DAGs (Astronomer-managed) that orchestrate dbt runs, data quality checks, and downstream dependencies reliably.
• Apply solid DAG design: idempotent tasks, proper backfill strategies, SLA alerting, and clean dependency graphs.
• Work in our Cosmos (dbt + Airflow) integration — you know when to use a DbtTaskGroup vs a custom operator.

Data quality & governance

• Implement data quality checks at every layer: freshness, null/uniqueness tests, referential integrity, distribution drift, and business-rule assertions.
• Drive data stewardship practices: ownership, SLAs, clear "source of truth" definitions, and change communication.
• Handle PII fields correctly — masking, anonymization, and access-tier alignment. Compliance experience (SOC 2, ISO 27001, or similar) is a meaningful plus.

Stakeholder management

• Be the analytical partner to Finance, GTM, Product, and Engineering — translate business questions into durable data models, not one-off queries.
• Drive alignment on metric definitions, data ownership, and delivery tradeoffs across stakeholders with competing priorities.
• Communicate data quality issues, model changes, and breaking changes proactively. You treat downstream consumers as customers.
• Write clear documentation — model descriptions, column-level lineage, and business context — so analysts can self-serve with confidence.
• Run or contribute to data reviews, data-driven planning discussions, and architecture reviews involving the warehouse.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $240,000 - $275,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

This is the first dedicated data hire on Together AI's Finance team. You will own the data layer that Finance runs on — building from scratch the models, pipelines, and reporting infrastructure that allow Strategic Finance, FP&A, and Accounting teams to get reliable answers quickly. The person in this role will have direct exposure to every part of the Finance organization and a real opportunity to shape how data-driven decision-making develops here as the company scales.

A significant portion of your work will touch the data behind the economics of Together's infrastructure, which sits behind nearly every financial question we ask. You will work closely with Together's Data and Commerce engineering team, which owns the underlying billing pipelines and data warehouse. Your job is to define and build the modeling and reporting layer that turns raw operational data into finance-grade datasets — aligning on data contracts, representing Finance's requirements in data design decisions, and ensuring the metrics Finance depends on are correct, documented, and trusted.

Responsibilities

• Own and evolve the dbt transformation layer for Finance: design, build, test, document, and maintain models covering billing, financial performance, compute unit economics, and operational metrics
• Author and maintain Airflow DAGs (Astronomer-managed) that orchestrate Finance dbt runs, data quality checks, and downstream dependencies reliably
• Deliver dashboards and reporting in Hex for the executive team covering financial performance, utilization, and key operating metrics
• Partner with Strategic Finance, FP&A, and Accounting teams on the data infrastructure behind forecasting, cost modeling, and other financial analyses
• Set data quality standards across Finance data products and own incident response when Finance-critical pipelines break
• Build the data foundation – clean, well-structured, documented, and reliably maintained – that enables Finance team to self-serve data analysis and supports AI automation and agentic workflows 

Requirements

• 5+ years in an analytics engineering or data engineering role, with meaningful time supporting Finance or business operations teams
• Expert SQL and production-grade dbt experience — models, tests, docs, snapshots, incremental strategies; you've designed a dbt project from scratch and maintained it
• Hands-on experience with Snowflake and Airflow in production; familiarity with Astronomer and the Cosmos dbt integration is a strong plus
• Solid dimensional modeling fundamentals: star schemas, slowly changing dimensions, fact table grain — you can apply Kimball principles without needing to look them up
• Strong dashboarding skills with a track record of executive-facing reporting that people actually use; experience with Hex or a comparable notebook/BI tool
• Clear communicator who can align stakeholders on metric definitions and translate between engineering tradeoffs and Finance requirements in both directions
• High comfort with ambiguity; this role will require scoping problems from scratch, not executing against pre-defined specs

Nice to Have

• Experience with financial data or billing data such as ARR, usage-based billing, invoice reconciliation, revenue recognition patterns, etc.. We operate a usage-based billing system and this context transfers directly.
• Experience with PII handling, data masking, access-tier modeling, or compliance work (SOC 2, ISO 27001, GDPR, CCPA).
• Familiarity with lakehouse patterns (Iceberg, Delta, Hudi) and hybrid warehouse/lake architectures.
• Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.
• Experience with Hex, Metabase, or similar notebook/BI tooling that sits on top of your dbt models.
• Prior experience in a high-growth AI/ML infrastructure or platform company

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200k -$240k + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy.  

We are looking for a Senior Data Engineer to join our Data & ML Platform team, responsible for development, maintenance and support for Oura’s Datalake and adjacent systems, collaborating closely with data scientists, analysts and other departments utilizing the Datalake.

This is a hybrid role based in San Francisco, CA, working onsite 1-2 days per week.

We have offices in San Francisco, San Diego and Los Angeles for those who prefer hybrid or office settings. Oura employees in other major cities (like Boston and New York) occasionally gather informally at local co-working locations.

What you will do: 

• Build, operate, and improve Oura’s Datalake consisting of systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as AWS Kinesis, S3, Spark / Glue, Athena, dbt, Iceberg, Snowflake, Docker, workflow engines, and more.
• Design and implement data models and pipelines with a strong focus on data quality, reliability, and governance.
• Ensure that our data platform and processes meet privacy, compliance, and security requirements.
• Build components that support the handling of datasets, training, testing, and release of new on-device and cloud-based ML models.
• Independently collaborate with different stakeholders including Data Scientists, Testing, Firmware, and Hardware to define and implement improvements and new functionality and support internal Datalake consumers in their day-to-day work.
• Write code, mostly in Python and SQL  with occasional additions Typescript, Java or some other language.

We would love to have you on our team if you have:

• 5+ years of experience developing and operating production systems.
• Experience running, monitoring, and debugging production systems at scale on a public cloud. We rely on AWS but experience with other cloud platforms counts too.
• Good architectural understanding of event-driven architectures, workflow engines, database, and data warehouse systems.
• Ability to design robust data models and pipelines, with attention to data accuracy and integrity.
• Experience in building infrastructure and components following best practices such as CI/CD and infrastructure as code.
• Demonstrated skills in writing well-structured, testable, and high-performance code.
• Familiarity with some of the following: Workflow engines, Stream processing, MLops, Spark, Athena, SQL, dbt, Databricks.
• You are self-motivated, proactive, and able to lead and manage your own work effectively.
• A pragmatic and goal oriented approach to development.

What Makes You Stand Out

• Real-life experience with Databricks.
• Familiarity and experience with the Data Mesh approach
• Broad knowledge of software fundamentals, databases, warehouses, and system design with experience on various programming languages

Benefits 

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own plus employee discounts for friends & family
• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
• Paid sick leave and parental leave

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 1 $172,550 - $203,000
• Region 2 $159,000 - $187,000
• Region 3 $148,000 - $174,000

A recruiter can determine your zones/tiers based on your US location.

About the Role

This role is for someone who wants to own the technical win. As a Senior Enterprise Solutions Engineer at Hightouch, you will partner with your Account Executives to drive the full technical sales motion from deep discovery and architectural solutioning to tailored product demonstrations and rigorous technical validation. You will own relationships with technical champions, co-develop account strategy, and guide customers to our solutions by navigating complex, multi-stakeholder buying committees and running competitive enterprise sales cycles. We leverage a disciplined value-selling motion, and are looking for deep experience in enterprise sales cycles where you have had to earn the technical win, not assume it.

Hightouch sits at the intersection of two powerful technological shifts: the rise of agentic AI and the maturation of the cloud data warehouse. We are solving real, complex problems at the intersection of marketing and data. As a senior SE, you will become a product expert, a trusted advisor to enterprise buyers, and a meaningful contributor to a team that is still early in building something significant.

What You’ll Do

• Lead technical discovery to deeply understand a customer’s data architecture, marketing workflows, and business objectives; and translate that into differentiated requirements and a compelling solution design.
• Design and deliver tailored product demonstrations and architectural solutions spanning Hightouch’s Customer Studio, Identity Resolution, Match Booster, and Agentic Marketing Platform.
• Run proof-of-concept engagements end-to-end: scoping, designing, executing, and validating with the discipline and rigor required to close complex enterprise deals.
• Build deep technical relationships with data engineers, architects, and marketing technologists becoming their trusted advisor.
• Navigate complex buying committees, engaging confidently with technical teams, marketing leaders, and C-suite executives

What Success Looks Like

Quickly build technical expertise, moving from foundational product, use case, and demo fluency in the first three months to independently closing deals and solving complex, multi-product problems within six months. You will begin contributing beyond your own deals and raising the collective bar for the team within a year.

What We’re Looking For

Required

• 7+ years of progressive enterprise pre-sales or solutions engineering experience, including complex solution architecture across multi-stakeholder buying cycles.
• Demonstrated ability to lead technical discovery, architectural whiteboarding, and solution design with both technical and business audiences, including C-suite stakeholders.
• Deep familiarity with modern data ecosystems: cloud data warehouses, data modeling, data engineering, integrations, and APIs - and the ability to navigate a customer’s data architecture confidently without needing to be a hands-on practitioner.
• Proven ability to build technical champions and influence complex buying committees across engineering, marketing, and executive levels.
• Experience in competitive enterprise sales motions. Familiarity with MEDDPICC, Command the Message, or equivalent value-selling frameworks is a strong plus.
• Intellectual curiosity, high ambition, and humility. You want to keep getting better, and you are honest about what you do not yet know.
• A team-first orientation where you elevate the people around you, operate within shared frameworks and processes, and measure yourself by more than your own quota.

Bonus

• Hands-on experience with Customer Data Platforms (CDPs), Marketing Automation, Data Warehouses, or similar technologies at the integration, architecture, or use case level.
• Background collaborating with data engineering, science, or analytics teams, either as a customer or in a prior role.
• Experience in a high-growth B2B SaaS company scaling through a significant inflection point.

Why Hightouch

We are building something that has the potential to redefine how companies use data to drive marketing outcomes. We’ve doubled in size each of the last three years, earned recognition as a Gartner Magic Quadrant leader in CDP, and have been acknowledged in the top 10 of the Forbes Best Startups list the last two years.

Beyond the market position and the customer list, what makes this team worth joining is the culture and values. Two core values exemplify how this team operates:

Forever Hungry — We are ambitious and we celebrate wins, but we are never fully satisfied. We are always looking for ways to push further, move faster, and do more for our customers and each other.

Raising the Bar — We have high expectations for performance and believe in having exceptional talent in every position. We look deeper than credentials, prioritize trajectory over pedigree, and invest in people who make everyone around them better.

As a senior SE at Hightouch, you will have the autonomy to shape your territory, the product complexity to do technically meaningful work, and a team around you that makes it worth showing up for.

Compensation

On-Target Earnings: $220,000–$270,000 annually
Base Salary: $154,000–$189,000 annually

We also offer meaningful equity compensation in the form of ISO options, with early exercise and a generous 10-year post-termination exercise window.

* Travel required for customer and team engagements.

As a Data Engineer on our BI team, you’ll be a key player in Motive’s growth, delivering the data infrastructure for the AI era. You’ll act as the essential link between complex data and key business domains, delivering the high-quality datasets and semantic models that drive global strategy. This is an exciting opportunity to implement cutting-edge tooling, leverage AI to enhance your workflow, and master a modern data stack in a fast-evolving environment.

This is the perfect role for a "jack of all trades" data practitioner. You’ll design data models, build robust pipelines, manage DevOps and automated systems, and implement AI-driven data tooling. You’ll even get your hands dirty building dashboards and performing deep-dive analysis. If you love working full-stack and owning the entire data lifecycle, you’ll love this role.

What You'll Do:

• Collaborate & Strategize: Partner closely with business stakeholders to understand their challenges and design end-to-end architecture that solves complex business problems.
• Build & Maintain Data Models: Design, develop, and own robust, efficient, and scalable data models in Snowflake and Iceberg using dbt and advanced SQL.
• Orchestrate & Automate: Build and manage reliable data pipelines and CI/CD workflows using tools like Airflow, Python, and Terraform to ensure data is fresh, trustworthy, and infrastructure is version-controlled.
• Champion Data Quality: Implement rigorous testing, documentation, and data governance practices to maintain a single source of truth.
• Enable Analytics & Workflows: Act as the Product Owner and Tech Lead for your data domains, taking responsibility for the end-to-end data product delivery– from raw ingestion to data models enabling analytics and data apps in tools like Tableau and Retool.
• Innovate with AI: Help us build our next-generation data infrastructure by integrating AI capabilities (like Snowflake Cortex AI) to democratize analytics and empower the business.
• Architect Observability: Implement monitoring and alerting frameworks (e.g., dbt packages or  Monte Carlo monitors) to proactively catch "silent" data failures before stakeholders do.

What We're Looking For:

• 6+ years of experience in Analytics Engineering, Data Engineering, or a similar role.
• Deep expertise in SQL and developing complex data models for analytical purposes (e.g., dimensional modeling).
• Hands-on experience with:
  • Data Warehousing: High proficiency in Snowflake (preferred) and experience with Open Table Formats like Iceberg.
  • Data Transformation: dbt
  • Orchestration & ETL: Airflow, Fivetran, Airbyte
  • Cloud Platform: AWS
  • Programming/Ingestion: Python
  • Infrastructure as Code: Terraform
  • AI-Augmented Development: Proficiency using AI coding assistants (Cursor, Copilot, or Claude) to accelerate development and automate routine tasks.
• A strong analytical mindset with a proven ability to solve ambiguous business problems with data.
• Excellent communication skills and experience working cross-functionally.
• Self-starter with the ability to self-project manage work
• A user focus with the ability to understand how a data consumer will use the data products you build

Bonus Points (Nice-to-Haves)

• Experience building semantic models for natural language querying
• Direct experience with advanced Snowflake features (e.g., Snowpark, Cortex AI).
• Experience building visualizations and dashboards in tools like Tableau,  Retool, or Thoughtspot.

About the Role

This role is for someone who wants to own the technical win. As a Mid-Market Solutions Engineer at Hightouch, you will partner with your Account Executives to drive the full technical sales motion from deep discovery and architectural solutioning to tailored product demonstrations and rigorous technical validation. You will own relationships with technical champions, co-develop account strategy, and guide customers to our solutions by navigating complex, multi-stakeholder buying committees and running competitive enterprise sales cycles. We leverage a disciplined value-selling motion, and are looking for deep experience in sales cycles where you have had to earn the technical win, not assume it.

What You’ll Do

• Lead technical discovery to deeply understand a customer’s data architecture, marketing workflows, and business objectives; and translate that into differentiated requirements and a compelling solution design.
• Design and deliver tailored product demonstrations and architectural solutions spanning Hightouch’s suite of products.
• Run proof-of-concept engagements end-to-end: scoping, designing, executing, and validating with the discipline and rigor required to close complex enterprise deals.
• Build deep technical relationships with data engineers, architects, and marketing technologists becoming their trusted advisor.
• Navigate complex buying committees, engaging confidently with technical teams, marketing leaders, and C-suite executives

What Success Looks Like

Quickly build technical expertise, moving from foundational product, use case, and demo fluency in the first three months to independently closing deals and solving complex, multi-product problems within six months. You will begin contributing beyond your own deals and raising the collective bar for the team within a year.

What We’re Looking For

Required

• 2+ years of progressive mid-market pre-sales or solutions engineering experience, including complex solution architecture across multi-stakeholder buying cycles.
• Demonstrated ability to lead technical discovery, architectural whiteboarding, and solution design with both technical and business audiences, including C-suite stakeholders.
• Deep familiarity with modern data ecosystems: cloud data warehouses, data modeling, data engineering, integrations, and APIs - and the ability to navigate a customer’s data architecture confidently without needing to be a hands-on practitioner.
• Proven ability to build technical champions and influence complex buying committees across engineering, marketing, and executive levels.
• Experience in competitive sales motions. Familiarity with MEDDPICC, Command the Message, or equivalent value-selling frameworks is a strong plus.
• Intellectual curiosity, high ambition, and humility. You want to keep getting better, and you are honest about what you do not yet know.
• A team-first orientation where you elevate the people around you, operate within shared frameworks and processes, and measure yourself by more than your own quota.

Bonus

• Hands-on experience with Customer Data Platforms (CDPs), Marketing Automation, Data Warehouses, or similar technologies at the integration, architecture, or use case level.
• Background collaborating with data engineering, science, or analytics teams, either as a customer or in a prior role.
• Experience in a high-growth B2B SaaS company scaling through a significant inflection point.

Why Hightouch

We are building something that has the potential to redefine how companies use data to drive marketing outcomes. We’ve doubled in size each of the last three years, earned recognition as a Gartner Magic Quadrant leader in CDP, and have been acknowledged in the top 10 of the Forbes Best Startups list the last two years.

Beyond the market position and the customer list, what makes this team worth joining is the culture and values. Two core values exemplify how this team operates:

Forever Hungry — We are ambitious and we celebrate wins, but we are never fully satisfied. We are always looking for ways to push further, move faster, and do more for our customers and each other.

Raising the Bar — We have high expectations for performance and believe in having exceptional talent in every position. We look deeper than credentials, prioritize trajectory over pedigree, and invest in people who make everyone around them better.

As an SE at Hightouch, you will have the autonomy to shape your territory, the product complexity to do technically meaningful work, and a team around you that makes it worth showing up for.

Compensation

On-Target Earnings: $160,000–$220,000 annually

Base Salary: $112,000–$154,000 annually

We also offer meaningful equity compensation in the form of ISO options, with early exercise and a generous 10-year post-termination exercise window.

About the Role

This role is for someone who wants to own the technical win. As an Enterprise Solutions Engineer at Hightouch, you will partner with your Account Executives to drive the full technical sales motion from deep discovery and architectural solutioning to tailored product demonstrations and rigorous technical validation. You will own relationships with technical champions, co-develop account strategy, and guide customers to our solutions by navigating complex, multi-stakeholder buying committees and running competitive enterprise sales cycles. We leverage a disciplined value-selling motion, and are looking for deep experience in enterprise sales cycles where you have had to earn the technical win, not assume it.

Hightouch sits at the intersection of two powerful technological shifts: the rise of agentic AI and the maturation of the cloud data warehouse. We are solving real, complex problems at the intersection of marketing and data. As a senior SE, you will become a product expert, a trusted advisor to enterprise buyers, and a meaningful contributor to a team that is still early in building something significant.

What You’ll Do

• Lead technical discovery to deeply understand a customer’s data architecture, marketing workflows, and business objectives; and translate that into differentiated requirements and a compelling solution design.
• Design and deliver tailored product demonstrations and architectural solutions spanning Hightouch’s Customer Studio, Identity Resolution, Match Booster, and Agentic Marketing Platform.
• Run proof-of-concept engagements end-to-end: scoping, designing, executing, and validating with the discipline and rigor required to close complex enterprise deals.
• Build deep technical relationships with data engineers, architects, and marketing technologists becoming their trusted advisor.
• Navigate complex buying committees, engaging confidently with technical teams, marketing leaders, and C-suite executives

What Success Looks Like

Quickly build technical expertise, moving from foundational product, use case, and demo fluency in the first three months to independently closing deals and solving complex, multi-product problems within six months. You will begin contributing beyond your own deals and raising the collective bar for the team within a year.

What We’re Looking For

Required

• 5+ years of progressive enterprise pre-sales or solutions engineering experience, including complex solution architecture across multi-stakeholder buying cycles.
• Demonstrated ability to lead technical discovery, architectural whiteboarding, and solution design with both technical and business audiences, including C-suite stakeholders.
• Deep familiarity with modern data ecosystems: cloud data warehouses, data modeling, data engineering, integrations, and APIs - and the ability to navigate a customer’s data architecture confidently without needing to be a hands-on practitioner.
• Proven ability to build technical champions and influence complex buying committees across engineering, marketing, and executive levels.
• Experience in competitive enterprise sales motions. Familiarity with MEDDPICC, Command the Message, or equivalent value-selling frameworks is a strong plus.
• Intellectual curiosity, high ambition, and humility. You want to keep getting better, and you are honest about what you do not yet know.
• A team-first orientation where you elevate the people around you, operate within shared frameworks and processes, and measure yourself by more than your own quota.

Bonus

• Hands-on experience with Customer Data Platforms (CDPs), Marketing Automation, Data Warehouses, or similar technologies at the integration, architecture, or use case level.
• Background collaborating with data engineering, science, or analytics teams, either as a customer or in a prior role.
• Experience in a high-growth B2B SaaS company scaling through a significant inflection point.

Why Hightouch

We are building something that has the potential to redefine how companies use data to drive marketing outcomes. We’ve doubled in size each of the last three years, earned recognition as a Gartner Magic Quadrant leader in CDP, and have been acknowledged in the top 10 of the Forbes Best Startups list the last two years.

Beyond the market position and the customer list, what makes this team worth joining is the culture and values. Two core values exemplify how this team operates:

Forever Hungry — We are ambitious and we celebrate wins, but we are never fully satisfied. We are always looking for ways to push further, move faster, and do more for our customers and each other.

Raising the Bar — We have high expectations for performance and believe in having exceptional talent in every position. We look deeper than credentials, prioritize trajectory over pedigree, and invest in people who make everyone around them better.

As a senior SE at Hightouch, you will have the autonomy to shape your territory, the product complexity to do technically meaningful work, and a team around you that makes it worth showing up for.

Compensation

On-Target Earnings: $190,000–$250,000 annually
Base Salary: $133,000–$175,000 annually

We also offer meaningful equity compensation in the form of ISO options, with early exercise and a generous 10-year post-termination exercise window.

* Travel required for customer and team engagements.

About the Role

This role is for someone who wants to own the technical win. As an Enterprise Solutions Engineer at Hightouch, you will partner with your Account Executives to drive the full technical sales motion from deep discovery and architectural solutioning to tailored product demonstrations and rigorous technical validation. You will own relationships with technical champions, co-develop account strategy, and guide customers to our solutions by navigating complex, multi-stakeholder buying committees and running competitive enterprise sales cycles. We leverage a disciplined value-selling motion, and are looking for deep experience in enterprise sales cycles where you have had to earn the technical win, not assume it.

Hightouch sits at the intersection of two powerful technological shifts: the rise of agentic AI and the maturation of the cloud data warehouse. We are solving real, complex problems at the intersection of marketing and data. As a senior SE, you will become a product expert, a trusted advisor to enterprise buyers, and a meaningful contributor to a team that is still early in building something significant.

What You’ll Do

• Lead technical discovery to deeply understand a customer’s data architecture, marketing workflows, and business objectives; and translate that into differentiated requirements and a compelling solution design.
• Design and deliver tailored product demonstrations and architectural solutions spanning Hightouch’s Customer Studio, Identity Resolution, Match Booster, and Agentic Marketing Platform.
• Run proof-of-concept engagements end-to-end: scoping, designing, executing, and validating with the discipline and rigor required to close complex enterprise deals.
• Build deep technical relationships with data engineers, architects, and marketing technologists becoming their trusted advisor.
• Navigate complex buying committees, engaging confidently with technical teams, marketing leaders, and C-suite executives

What Success Looks Like

Quickly build technical expertise, moving from foundational product, use case, and demo fluency in the first three months to independently closing deals and solving complex, multi-product problems within six months. You will begin contributing beyond your own deals and raising the collective bar for the team within a year.

What We’re Looking For

Required

• 5+ years of progressive enterprise pre-sales or solutions engineering experience, including complex solution architecture across multi-stakeholder buying cycles.
• Demonstrated ability to lead technical discovery, architectural whiteboarding, and solution design with both technical and business audiences, including C-suite stakeholders.
• Deep familiarity with modern data ecosystems: cloud data warehouses, data modeling, data engineering, integrations, and APIs - and the ability to navigate a customer’s data architecture confidently without needing to be a hands-on practitioner.
• Proven ability to build technical champions and influence complex buying committees across engineering, marketing, and executive levels.
• Experience in competitive enterprise sales motions. Familiarity with MEDDPICC, Command the Message, or equivalent value-selling frameworks is a strong plus.
• Intellectual curiosity, high ambition, and humility. You want to keep getting better, and you are honest about what you do not yet know.
• A team-first orientation where you elevate the people around you, operate within shared frameworks and processes, and measure yourself by more than your own quota.

Bonus

• Hands-on experience with Customer Data Platforms (CDPs), Marketing Automation, Data Warehouses, or similar technologies at the integration, architecture, or use case level.
• Background collaborating with data engineering, science, or analytics teams, either as a customer or in a prior role.
• Experience in a high-growth B2B SaaS company scaling through a significant inflection point.

Why Hightouch

We are building something that has the potential to redefine how companies use data to drive marketing outcomes. We’ve doubled in size each of the last three years, earned recognition as a Gartner Magic Quadrant leader in CDP, and have been acknowledged in the top 10 of the Forbes Best Startups list the last two years.

Beyond the market position and the customer list, what makes this team worth joining is the culture and values. Two core values exemplify how this team operates:

Forever Hungry — We are ambitious and we celebrate wins, but we are never fully satisfied. We are always looking for ways to push further, move faster, and do more for our customers and each other.

Raising the Bar — We have high expectations for performance and believe in having exceptional talent in every position. We look deeper than credentials, prioritize trajectory over pedigree, and invest in people who make everyone around them better.

As a senior SE at Hightouch, you will have the autonomy to shape your territory, the product complexity to do technically meaningful work, and a team around you that makes it worth showing up for.

Compensation

On-Target Earnings: $190,000–$250,000 annually
Base Salary: $133,000–$175,000 annually

We also offer meaningful equity compensation in the form of ISO options, with early exercise and a generous 10-year post-termination exercise window.

* Travel required for customer and team engagements.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Role 

We’re looking for a Senior Data Engineer to design, build, and operate the data pipelines and aggregates that power Zeta’s AdTech platform. This is a hands-on individual contributor role focused on high-scale batch + streaming data processing, reliable data products, and analytics-ready datasets that enable prediction, agentic workflows, BI reporting, and measurement. You will partner closely with backend, ML, and product teams to deliver trusted, well-modeled data with strong performance, quality, and observability. 

What You’ll Do 

• Build data pipelines: Develop robust batch and streaming pipelines (Kafka/Kinesis) to ingest, transform, and enrich large-scale event data (impressions, clicks, conversions, costs, identity signals). 

• Create data aggregates & marts: Design and maintain curated aggregates and dimensional models for multiple consumers—prediction models, agents, BI dashboards, and measurement workflows. 

• Data modeling & contracts: Define schemas, data contracts, and versioning strategies to keep downstream systems stable as sources evolve. 

• Data quality & reliability: Implement validation, anomaly detection, backfills, and reconciliation to ensure completeness, correctness, and timeliness (SLAs/SLOs). 

• Performance & cost optimization: Optimize compute/storage for scale (partitioning, file sizing, incremental processing, indexing), balancing latency, throughput, and cost. 

• Orchestration & automation: Build repeatable workflows with scheduling/orchestration (e.g., Airflow, Dagster, Step Functions) and CI/CD for data pipelines. 

• Observability for data systems: Instrument pipelines with metrics, logs, lineage, and alerting to accelerate detection and root-cause analysis of data issues.
• Security & governance: Apply least-privilege access, PII-aware handling, and governance controls aligned with enterprise standards.

Qualifications

• 5+ years building production data pipelines and data products (batch and/or streaming) in a high-scale environment.
• Strong experience with SQL and data modeling (dimensional modeling, star/snowflake schemas, event modeling). 

• Hands-on experience with streaming systems (Kafka preferred) and/or AWS Kinesis, including event-driven designs. 

• Proficiency in one or more languages used for data engineering (Python, Java, Scala, or Go). 

• Experience with distributed data processing (Spark, Flink, or equivalent) and performance tuning at scale. 

• Experience with AWS data services and cloud-native patterns (S3, Glue/EMR, Athena, Redshift, etc. as applicable). 

• Familiarity with lakehouse/table formats and large-scale storage patterns (e.g., Parquet; Iceberg/Hudi/Delta are a plus). 

• Experience with orchestration/workflow tooling (Airflow/Dagster/Step Functions) and CI/CD for data workloads. 

• Strong data quality/observability practices (tests, monitoring, lineage; understanding of SLAs/SLOs). 

• Experience with SQL + NoSQL data stores (e.g., Postgres/MySQL; DynamoDB/Cassandra/Redis) and choosing the right store per use case.
• Clear communicator and collaborator; able to work with mixed audiences and translate needs into reliable data interfaces. 

Preferred Experience

• AdTech / programmatic advertising domain knowledge: DSP/SSP/exchange/RTB concepts and data flows. 

• Experience building measurement pipelines (attribution, incrementality, lift, or experimentation analytics).
• Experience supporting ML feature stores, offline/online feature generation, or model training datasets. 

• Experience with real-time analytics stores (Druid/ClickHouse/Pinot) and high-cardinality aggregation strategies. 

• Deep knowledge of data governance/privacy, including PII handling and consent-aware data processing. 

• Open-source contributions, publications, or conference speaking. 

• BS/MS in CS/Engineering or equivalent practical experience. 

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $165,000 - $175,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases

#LI-YW1

The Customer Problem

When you open Spotify, the homepage is different for every user. When you browse Nike's site, products are ranked by what Nike thinks you'll buy. When you log into Chase, offers are tailored to your spending. This is web and mobile personalization: deciding in real time what each customer sees inside your product. It directly moves conversion, retention, and revenue at the point where customers are already engaged.

Almost nobody does it well outside of companies that build it from scratch. A single experiment (testing whether high-spend users convert better seeing a loyalty upsell on the account page) requires an analyst to build the segment, a PM to write targeting rules, a designer to create variants, an engineer to instrument the test, and someone to monitor results. Most teams run 5–10 per quarter and end up with a handful of static rules covering a fraction of their users.

The tools that exist (Optimizely, Adobe Target) handle infrastructure but don't solve the coordination problem. Every experiment, audience, and piece of content still requires manual configuration. They also force companies to duplicate customer data into a proprietary store, adding months of implementation and permanent vendor lock-in.

Why Agents are the Solution

The shift from "AI assists a step" to "AI owns a workflow" is already happening in software engineering. Personalization is ready for the same shift.

Today: A growth team testing whether high-intent visitors convert better with a comparison page spends 2–4 weeks coordinating across tools and people. They run maybe 8 experiments that quarter.

With agents: The growth lead describes the goal. An agent identifies the audience from existing customer data, generates variants informed by past performance, configures the experiment with holdout groups, launches it, monitors significance, and reallocates traffic. The human reviews before launch. Calendar time: hours. The same team runs 50+ experiments per quarter because the coordination cost drops to nearly zero.

Agents handle the full chain as one workflow: audience, content, experiment, optimization. Instead of a bunch of manual steps, agents rethink this as a continuously improving closed loop.

Why Hightouch, Why Now

More than 1,000 enterprises—like Domino’s, Chime, Spotify, Ramp, Whoop, Grammarly, use Hightouch to run their marketing. Earlier this year we launched the Agentic Marketing Platform with two pillars:

• Agentic Advertising Studio. Agents analyze performance, competitor creative, and brand guidelines, then assemble ad concepts across Meta, Google, TikTok, and LinkedIn.
• Agentic Lifecycle Studio. Agents identify lifecycle opportunities, draft audiences, assemble on-brand email and SMS campaigns, and orchestrate them through Braze, Iterable, Salesforce, and Adobe.

Advertising covers paid media. Lifecycle covers email, SMS, and push. Agentic Personalization is the third pillar: what customers experience inside the website and mobile app. Different buyer (product and growth teams), different workflow (real-time experimentation), different technical surface (browser SDKs and edge delivery). Same agent infrastructure and data foundation.

What no competitor can replicate:

• Agent orchestration. 25+ specialized skills for audience building, content generation, campaign analysis, and multi-step workflow coordination.
• Content assembly. Agents search existing asset libraries for reusable on-brand content before generating anything new, which is what makes output trustworthy enough for enterprises to ship.
• Marketing and brand context. Persistent layer connecting customer data, brand guidelines, creative assets, and performance history so agents operate grounded in how the business works.
• Real-time data infrastructure. Low-latency personalization API, sub-second audience evaluation, ML-powered optimization and recommendations, event pipeline processing millions of events daily.

The Role

Founding Product Manager for Agentic Personalization: Hightouch's third major pillar and biggest new investment. You define the product, the sequencing, and the go-to-market.

• Customer discovery. Deep engagement with product and growth teams at enterprise companies to understand how they personalize web and mobile today, and what would earn their trust in an agent-driven approach. Translate into a roadmap tied to revenue milestones.
• Define the agent experience. What agents do autonomously (segments, variants, experiments, traffic allocation) vs. what needs human approval (production launches, brand-sensitive content). Design the feedback loop that builds trust over time.
• Scale the GTM. Co-own pipeline, join customer calls, shape competitive positioning, partner with CS on implementation playbooks.

High-visibility role working directly with founders and executive team.

What We're Looking For

• Zero-to-one track record. Products you built from nothing to meaningful revenue, ideally at a B2B SaaS company. Domain matters less than evidence you can find product-market fit under uncertainty.
• Technical depth. Can evaluate architectural tradeoffs, debate infrastructure decisions with senior engineers, and reason about things like batch vs. real-time and caching strategies at the level of product decisions.
• Commercial instinct. Think in terms of pipeline, conversion, and expansion. Build roadmaps that map to revenue targets.
• Speed. Small team, high autonomy, tight cycles. We use AI heavily in our own workflows.
• Cross-functional trust. This spans engineering, design, sales, CS, and leadership. You drive clarity from ambiguity.

We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $240,000 - $320,000 USD per year, which is location independent in accordance with our remote-first policy. We also offer meaningful equity compensation in the form of ISO options, and offer early exercise and a 10 year post-termination exercise window.

The Problem

Every large advertiser runs the same loop: strategist reviews performance data, decides what to test next, briefs a designer, waits for assets, hands them to a media buyer who builds campaigns across Meta and Google and TikTok, launches, monitors, repeats. The process is slow because creative production, campaign management, and performance analysis happen in three separate systems, and insights travel between them through decks, Slack threads, and weekly syncs.

Companies like Nike, Uber, and PepsiCo spend millions per month on digital ads and employ entire teams just to keep this loop turning. Most teams run 10 to 15 creative tests per month because every test requires manual work across multiple tools and teams. The result: most ad spend runs against stale creative, performance degrades from fatigue, and the gap between "what's working" and "what gets made next" is measured in weeks.

Why Agents Change This

Advertising is uniquely high-leverage for AI agents because nearly every step in the workflow is now automatable, and the steps compound:

• Research. Agents can continuously monitor competitor ad libraries, auto-classify creative by format, hook, and message, and surface positioning gaps. What used to require a strategist spending hours in Meta Ad Library happens in the background, always current.
• Creative production. Generative models can now produce ad-quality images and video. The constraint has shifted from "can AI make this" to "can AI make this on-brand and on-spec for each platform." That is a solvable engineering problem, not a research problem.
• Campaign structure. Building properly structured campaigns (naming conventions, audience splits, placement targeting, budget allocation) across five ad platforms is tedious, rules-based work. Agents can do it faster and more consistently than humans.
• Optimization. Detecting creative fatigue, reallocating budget toward winners, and knowing when to rotate in fresh variants is pattern recognition across structured data. Agents excel at exactly this.
• The compounding effect. When one agent handles the full chain (research, production, activation, analysis, iteration) as a single workflow, the cycle time collapses from weeks to hours. A team that runs 15 tests per month can run 50+, not because any individual step got faster, but because the coordination cost between steps drops to nearly zero.

Today: A performance marketing team testing new concepts on Meta and TikTok spends 2 to 3 weeks per cycle.

With agents: The marketing lead describes the objective. An agent analyzes recent performance, identifies the highest-value concepts to test, generates on-brand variants across formats, builds campaigns, launches after human approval, monitors results, detects fatigue, and queues replacements. Same team, 5x to 7x the testing volume, because the human bottleneck becomes strategy and judgment, not execution.

Why Hightouch, Why Now

Hightouch built the Agentic Marketing Platform: one system where AI agents own entire marketing workflows across lifecycle (email, SMS, push through Braze, Iterable, Salesforce, Adobe), advertising (creative production and activation across paid channels), and product experiences (real-time web and mobile experimentation). All three surfaces share the same agent infrastructure, brand and customer context, and warehouse-native data foundation. An insight the ads agent learns about creative performance can inform what the lifecycle agent sends. That shared context across every marketing surface is the product.

Ads is already live, and demand is surging. Enterprise customers are generating ad creative today with agents that analyze performance across Meta, Google, TikTok, LinkedIn, and Snapchat, produce briefs grounded in competitive research and brand guidelines, and generate ready-to-ship ad concepts. Early adoption has been strong: customers who start using it quickly expand usage across campaigns and teams, and inbound interest from enterprise prospects is accelerating. The foundation works. The opportunity is building it into a platform that captures the full advertising workflow.

What Hightouch has that no competitor can replicate:

• Agent orchestration. 25+ specialized agent skills for audience building, content generation, campaign analysis, and multi-step workflow coordination, all composable into end-to-end workflows.
• Content assembly with brand trust. Agents search existing asset libraries for reusable on-brand content before generating anything new. This is what makes output trustworthy enough for enterprises to ship without heavy review cycles.
• Marketing and brand context. A persistent layer connecting customer data, brand guidelines, creative assets, competitive intelligence, and performance history so agents operate with full business context, not generic prompts.
• Warehouse-native data foundation. 62,000 workspaces, a million data syncs per day, 300+ integrations. Customer data stays in the warehouse. No proprietary data store, no duplication, no lock-in.

The Role

You will lead the Agentic Ads Platform. The foundation exists (customers generating ads today), and the opportunity is turning it into the platform that closes the full advertising loop. Four major areas of work:

• Multi-model creative generation. Today the platform generates static images. The roadmap includes video generation, motion graphics, format adaptation, and multi-model orchestration (routing to the best model for each task). Building a creative generation pipeline that produces broadcast-quality output across formats is a hard, high-value problem.
• Marketing context and brand adherence. Making agents genuinely trustworthy for enterprise creative teams. Better context engineering so agents follow brand guidelines, business rules, legal requirements, and channel-specific policies without constant human correction. The gap between "AI-generated ad" and "ad our brand team would actually approve" needs to shrink dramatically.
• Platform depth across ad channels. Deep integrations with Meta, Google, TikTok, LinkedIn, Snapchat, and others. Not just launching ads, but understanding each platform's creative specs, optimization levers, and best practices so agents can automatically adapt creative for each channel, syndicate content across platforms, and optimize placement-level performance. Think: an agent that knows a 9:16 video with text-safe zones works differently on TikTok Reels vs. Instagram Stories and adjusts accordingly.
• Best-in-class agentic creation experience. The interaction model for how marketers work with agents to go from objective to live campaign. This means the conversational interface, the review and approval workflows, the feedback loops that help agents learn what "good" looks like for each brand, and the progressive autonomy controls that let teams start with full human approval and graduate to agent-led execution as trust builds.

Day to day, you will:

• Run deep customer discovery with performance marketing and creative teams at enterprise companies. Understand their workflows, pain points, and what would earn their trust.
• Define the product roadmap tied to revenue milestones. Sequence what to build, what to compose from existing systems, and what to partner on.
• Ship product. Work directly with engineering and design on tight cycles.
• Co-own pipeline and go-to-market. Join customer calls, shape competitive positioning, partner with CS on implementation.

High-visibility role working directly with founders and executive team.

What We're Looking For

• Zero-to-one track record. You have built products from nothing to meaningful revenue, ideally at a B2B SaaS company. The domain matters less than evidence you can find product-market fit under uncertainty.
• Technical depth. You can evaluate architectural tradeoffs, reason about things like multi-model orchestration and API integration design at the level of product decisions, and hold your own in debates with senior engineers.
• Commercial instinct. You think in terms of pipeline, conversion, and expansion. You build roadmaps that map to revenue targets.
• Speed. Small team, high autonomy, tight cycles. We use AI heavily in our own workflows and expect you to do the same.
• Cross-functional trust. This role spans engineering, design, sales, CS, and leadership. You drive clarity from ambiguity.

About ROLLER

ROLLER is not your average software-as-a-service company. With a global presence in over 30 countries, we're here to bring some excitement to the leisure and attractions industry and make a difference! Our mission is to help businesses operate smoothly and create fun and memorable guest experiences by providing seamless ticketing, point-of-sale, self-serve kiosks, memberships and digital waiver processes.

But here's the best part: our team. We're a group of 300+ highly passionate, enthusiastic, and down-to-earth professionals located all around the world who are all working together to build something truly remarkable. We're aiming high and believe that the possibilities are endless. As we continue to grow globally, we're excited to write our success story and have fun along the way.

We genuinely love what we do, and we're looking for like-minded people to join us on this amazing journey. If you're ready to be part of a dynamic team and make a real impact, come aboard, and let's create some unforgettable experiences together at ROLLER!

About the Role

We are seeking a highly technical, hands-on Senior Data Engineer to architect and scale our data infrastructure from the ground up. As a core member of the data function within our Business Technology team, you will be responsible for building the pipelines and models that power smarter decision-making and operational efficiency across the entire organization.

In this foundational role, you will build & architect the modern data stack, ensuring our infrastructure is robust, automated, and governed. You collaborate as a technical partner with GTM ,Product, Finance, P&C to build high-performance data models and pipelines that transform raw data into actionable cross-functional insights.

Joining ROLLER at this pivotal growth stage, you will have the opportunity to make an outsized impact on our technical landscape, directly influencing how we process data to deliver world-class experiences for our customers globally.

What You'll Do

• Scalable Architecture: Design and implement robust Data Modeling and Architecture strategies that support high-volume data processing and maintain long-term scalability.
• Cloud Ecosystem: Develop and manage end-to-end data pipelines using Google Cloud Platform services, specifically leveraging Cloud Run, Cloud Function for compute, BigQuery for storage, and Cloud Composer (Airflow) for orchestration.
• Transformation Excellence: Build, maintain, and document complex data transformation layers using DBT (Data Build Tool) to ensure high data quality and reliability.
• Infrastructure as Code: Automate the provisioning of cloud resources using Terraform and streamline deployment workflows via GitHub Actions CI/CD pipelines.
• Cloud Data Warehousing: Demonstrate expert-level proficiency in managing and optimizing Cloud Data Warehouses, such as Snowflake & BigQuery.
• Team Collaboration: Partner with cross-functional stakeholders to build and scale high-performing data infrastructure that supports engineering, analytics, and Data Program needs.
• Stack Management: Architect and maintain a modern data stack by implementing best-in-class tools including Snowflake, Bigquery, dbt, Fivetran, Looker, Tableau and Airflow.
• Pipeline Engineering: Develop scalable ETL/ELT workflows and robust data models to deliver real-time analytics and unified business reporting.
• Data Visualization: Create and maintain intuitive, high-performance Looker dashboards will be an added advantage.

About You

You are a technical builder who views data as a competitive advantage. You thrive in fast-paced environments and have a proven track record of engineering scalable data foundations from the ground up. Equal parts architect and analytical problem-solver, you excel at balancing long-term technical vision with the daily hands-on execution of complex pipelines.

You are energized by the full lifecycle of data—moving beyond just writing code to actively leading project discovery and analysis alongside cross-functional partners. You take pride in enabling GTM, Product, Finance & P&C teams through clear insights and high-performance systems. Most importantly, you are excited to act as a founding technical force for a high-growth SaaS company that is transforming the guest experience for attractions businesses globally.

• 5+ years of experience in Data & Analytics or Data Engineering with a focus on Scalable cloud driven data pipeline build

• Proven experience in dimensional modeling (Star/Snowflake schema) and designing architectures that support both historical reporting and real-time needs.
• Expert-level proficiency in Snowflake or BigQuery, including performance tuning, cost optimization, and access control (RBAC).
• Hands-on experience with Google Cloud Platform services, specifically Cloud Function, Cloud Run for containerized workloads and Cloud Composer for orchestration.

• Through hands-on experience of dbt (Data Build Tool) to manage transformations, including writing custom macros, implementing tests, and generating documentation.
• Solid experience using Terraform to provision cloud resources, ensuring that infrastructure is version-controlled and reproducible.
• Proficiency in GitHub Actions to automate testing and deployment pipelines for data models and infrastructure.
• Ability to design high-performance dashboards that prioritize user experience and fast load times.

• Experience collaborating with Finance, GTM, and Product to define key metrics (like CAC, LTV, or Churn) and codifying them into the data layer.
• Familiarity with data ingestion tools like Fivetran , Airbyte, Workato, Mulesoft to sync data from various SaaS platforms into the warehouse.

• Operates as a full-stack Data Engineer with the technical authority to architect and build entire data lifecycles, from raw source ingestion to high-impact data visualization.
• Familiarity with business-critical systems like Salesforce, Chargbee, Gainsight, and product analytics tools.
• Strong communicator with a track record of working across technical and non-technical teams to drive alignment.
• You have a high appetite for Technology and AI and a natural curiosity for how it can transform your work. You’re comfortable using AI tools to automate repetitive 'busy work,' freeing you up to focus on high-impact work.

We believe AI is a career-defining inflection point. ROLLER is a fast adopter of new technology like AI, and every team member is empowered to own their learning and use the latest tools to supercharge their impact. We’re looking for candidates with the proficiency and curiosity to embrace AI and technology — not just as a technical skill, but as a core competency to help us achieve big goals

Preferred Qualifications

• Experience partnering with IT or Business Technology teams to drive cross-functional outcomes.
• Exposure to customer success and revenue workflows, such as onboarding journeys, renewal metrics, or support analytics.
• Familiarity with AI/ML pipelines and experimentation frameworks that support data-driven innovation.

Perks!

• You'll get to work on a category-leading product that customers love in a fun, high-growth industry! Check our Capterra and G2 reviews.
• ROLLER Recharge days to celebrate and recharge once we've hit our goals
• Engage in our 'Vibe Tribe' - led by our team members; you can contribute to company-wide initiatives directly. Regular events and social activities, fundraising & cause-related campaigns...you name it. We're willing to make it happen!
• Team Member Assistance Program to proactively support our team's health and wellbeing - access to coaching, education modules, weekly webinars, and more.
• 16 weeks paid Parental Leave for primary carers and 4 weeks paid Parental Leave for secondary carers.
• Work with a driven, fun, and switched-on team that likes to raise the bar in all we do!
• Individual learning & development budget plus genuine career growth opportunities as we continue to expand!

What You Can Expect

1. Initial call with our Talent Acquisition Manager
   You'll have an initial call with our Talent Acquisition Manager to chat through some of your experience to date, salary expectations and you can check off any initial questions you might have.
2. Interview with the Hiring Manager
   You'll get to meet with the hiring manager to learn more about the role & ROLLER whilst also talking through your experience in more detail.
3. Loop Interviews
   This is where you will get to meet our wider ROLLER team to do a 'vibe check' on us to make sure our culture & vibe meet what you are looking for!
4. Offer
   If all lights are green and the fit feel right, we'll conduct reference checks and you'll receive an offer to join!

Who we are 

In the past, to be a successful restaurateur, you simply had to have a passion for food and a passion for people - but to succeed as a digital restaurateur you also need to have a passion for technology. We believe in the joy of serving others, and that's why we created Otter – to help restaurateurs  succeed in online food delivery. Restaurants around the world, both large and small, including Chick-fil-A, Ben & Jerry’s, KFC, and Eataly trust our software to power their delivery business. We increase sales, reduce order issues, and decrease delivery headaches. 

What you’ll do

We are looking for a Head of Growth & Performance Marketing who operates at a world-class level — someone who can drive measurable revenue growth through disciplined experimentation, deep analytical insights, and mastery of paid acquisition channels.

• Own Otter’s global performance marketing strategy, spanning paid social, paid search, display, retargeting, and emerging channels.
  
  
• Manage and optimize $XM+ annual performance marketing budget with clear ROI and CAC efficiency targets.
  
  
• Build, scale, and continuously iterate on acquisition funnels across Meta Ads, Google Ads, and additional paid platforms.
  
  
• Develop a quantitative experimentation roadmap (A/B tests, landing page optimization, ad creative, audience segmentation).
  
  
• Partner with Product, Growth, Brand, and Sales to ensure full-funnel alignment and cross-functional acceleration.
  
  
• Own forecasting, spend pacing, weekly/monthly reporting, and insights for senior leadership.
  
  
• Drive attribution improvements using tools like GA4, Mixpanel, Looker, or Snowflake.
  
  
• Evaluate new channels, automation tools, and AI-powered optimization solutions to increase scale and lower CAC.
  
  
• Be a strategic thought partner to Otter’s leadership on overall growth strategy, channel mix, and long-term customer acquisition models.
  
  

What we’re looking for

• 10+ years in performance or growth marketing with direct ownership of a $M+ annual ad spend.
• Operator experience in a $50M+ ARR environment (SaaS, marketplace, high-growth startup, consumer goods or multi-market consumer tech).
• Deep expertise in Meta Ads and Google Ads, with a track record of scaling CAC-positive programs.
• Strong mathematical and analytical capability — comfortable in SQL, Excel, Looker, and funnel analytics.
• Proven ability to design full-funnel strategies and systematically improve every conversion point.
• Demonstrated ability to work in a high-growth, high-ambiguity environment with fast iteration cycles.
• Exceptional communication skills, with the ability to influence and present to senior stakeholders.

Why join us 

• Real impact: You will directly own one of the largest levers for Otter’s growth.
• Fast moving environment where great operators thrive.
• Opportunity to shape the future of restaurant technology.
• High ownership role with direct visibility to senior leadership across Otter and CSS.

What else you need to know

This role is based in our San Francisco office location. We believe that people do their best work when they are together. As a company, we’re in the marketplace of ideas and innovation. When you’re constantly innovating, changing how an industry works, inventing new products and processes - and we are doing all these things - we believe we’re better as a team in-person. That’s why all of our teams (except for our field-based roles) are now working from one of our office locations 5 days a week. Looking forward to sharing more about a Career of Substance at Otter.

The base salary range for this role is $182,000 - $214,000 per year.

Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.

Base salary is just one part of your total rewards package. You may also be eligible for equity awards and an annual performance-based bonus.

Benefits Summary (USA Full-Time Exempt Employees):

• Medical, dental, and vision insurance (multiple plans, incl. HSA options).
• Company-paid life and disability insurance (short- and long-term).
• Voluntary insurance: accident, critical illness, hospital indemnity.
• Optional supplemental life insurance for self, spouse, and children.
• Pet insurance discount.
• 401(k).
• Health Savings Account (HSA)
• Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
• Time Off policies:
• Discretionary vacation days
• 8 paid holidays per year
• Paid sick time
• Paid Bereavement leave
• Paid Parental Leave

Benefits are subject to change at the company's discretion.
CSS accepts applications on an ongoing basis.

Ready to join us as we serve those who serve others? 

#LI-Onsite

We are seeking a Senior Manager/Director of Technical Partner Solutions to define the strategic direction and lead the evolution of Braze's technical engagement with Technology (ISV) and Delivery Partners. This leader will scale the ISV function, focusing efforts on high-value technical partnerships and building a scalable support framework for technically complex customer use cases built by Delivery Partners.

This role requires a technical leader who can work cross-functionally to understand the technical needs of our partner ecosystem, map these needs against Braze's internal strategy, and translate them into measurable execution plans. You will work with Braze’s extensive ISV ecosystem alongside commercial counterparts managing this network. You will also work closely with the Partner Services Delivery team, who support our Delivery Partners to help with highly technical use cases, identify technical knowledge gaps, and recommend enablement plans for our Delivery Partners. You will manage a team of ISV Partner Managers and Partner Technical Advisors and advocate for the addition of further technical subject matter experts (such as AI Decisioning, Email Deliverability) within the Partner Services Technical Solutions function.

WHAT YOU'LL DO

• Collaborate with Partnerships to define ISV prioritization and execute ISV strategy in alignment with broader business goals at Braze, creating a clear and measurable partner onboarding and integration lifecycle management without sustained product dependency
• Strengthen cross-functional alignment with Product, Engineering, and Partnerships to ensure ISV integrations enhance customer value, accelerate product adoption, and support retention
• Oversee program scalability, introducing and managing tools and processes such as an Integration Platform as a Service (iPaaS), optimised partner listings, and documentation
• Demonstrate a data-oriented approach to define and track technical partner KPIs, such as integration quality (utilization, efficacy), number of new partners, speed to market,  time to integration, and technical certification rates
• Translate partner product updates, integration expansion requests, and complex customer use cases into actionable roadmap inputs for Product & Engineering
• Work closely with Product and Expert Services to identify upcoming product and new service launches and advise how Partner Services should support our partners with these new areas
• Lead and develop the Technical Partner Solutions overarching function, providing structure, mentorship, accountability, setting standards, and building processes and documentation. Establish and continuously evolve the job family, career development paths, and materials, and headcount model to ensure team engagement, scalability, and continuity
• Manage the ISV Partner Manager team to ensure integration SME coverage, meet troubleshooting SLAs, and provide ongoing technical support for Technology partners
• Manage the Partner Technical Advisor team to ensure comprehensive Braze product knowledge, technical subject matter expertise in new partner services such as Email Deliverability and AI Decisioning Studio, and provide ongoing technical oversight and support for Delivery partners
• Ability to craft a 12–24 month technical roadmap for partners that aligns with Braze’s long-term product vision. Define ongoing technical training requirements for Technology and Delivery partners and work with cross-functional stakeholders to execute on partner enablement plans
• Serve as the senior escalation point for partner-related IRTs and customer issues. Own cross-functional resolution with CX, Product, and Engineering
• Ability to resolve technical friction between Braze product teams and external partner engineering teams while maintaining trust
• Effective communication for rolling out new technical requirements or compliance standards across a global partner network

WHO YOU ARE

• 5–8+ years of experience in technical partner management, solutions engineering, partner engineering, or ISV program management at a SaaS or MarTech company; At least 3+ years in a leadership capacity
• Deep Technical Fluency: Expert knowledge of APIs (REST, webhooks), data integration patterns (ETL/reverse ETL, CDPs, event streaming), and hands-on comfort with data infrastructure tools (e.g., Snowflake, Segment, mParticle)
• Operational Excellence: Proven track record of building scalable processes—partner onboarding playbooks, tiered support models, and SLA frameworks—in a high-growth environment managing 100+ integrations. Comfortable operating in ambiguity and introducing structure without slowing innovation
• Strategic & Cross-functional Leadership: A systems thinker with the ability to strategically prioritize competing technical demands (inbound partner requests, integration expansion) with a clear rationale. Proven ability to influence and drive alignment across Product, Engineering, and GTM stakeholders
• Commercial Instinct: Experience connecting technical partnership work to revenue outcomes 
• Familiarity with iPaaS platforms, app marketplace/app store models, and self-service integration frameworks is a strong plus

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $110,000 and $182,000/year, with an expected On Target Earnings (OTE) between $129,000 and $214,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

The Global Data & Insights Team

Okta's Enterprise Data & Insights team powers the data infrastructure that drives decision-making across the company by building reliable pipelines, scalable data platforms, and production-grade data products. We partner closely with internal Data and Insights Analysts as well as external Okta Product teams to unlock business value through robust data architecture, efficient data movement, and the engineering foundations that make data trustworthy at scale.    

The Senior Analytics Engineer, Marketing Opportunity

We are seeking a Senior Analytics Engineer to serve as the technical architect of our marketing data engine. You will own our marketing attribution logic and end-to-end funnel performance data, evolving our current processes into an enterprise-grade ecosystem. Your mission is to uncover the high-fidelity signals that drive new customer acquisition and maximize expansion within our existing base. You’ll tackle a sophisticated roadmap of advanced analytics, transforming raw touchpoints into a trusted, scalable framework for growth.

This role sits at the intersection of business context and technical execution. You will design scalable data models, define consistent business logic, and help establish a strong semantic foundation that enables both human analytics and machine-driven intelligence.

You will partner closely with Marketing stakeholders, Data Analysts, Data Scientists, and Data Engineers to ensure data is accurate, consistent, and easy to consume; whether through dashboards, self-service exploration, or AI-powered workflows.

What you’ll be doing

Data Modeling & Semantics

• Design, build, and maintain scalable data models using dbt and Snowflake
• Define and standardize core Marketing metrics (e.g., pipeline, campaign performance, attribution, conversion rates)
• Establish consistent modeling patterns, naming conventions, and semantic clarity across datasets
• Contribute to a shared semantic layer that enables consistent reporting across channels and tools

AI-Ready Data & Snowflake Ecosystem

• Prepare high-quality, well-governed datasets for use with Snowflake Cortex and Snowflake Intelligence
• Enable data foundations that support LLM-powered use cases such as campaign insights, segmentation, and performance optimization
• Ensure data is context-rich, well-documented, and aligned with business meaning to improve AI accuracy and usability

Data Quality, Governance & Trust

• Implement robust testing, validation, and documentation practices in dbt
• Ensure consistency across dashboards and marketing tools through shared definitions and reusable models
• Apply data governance best practices, including access controls, lineage, and auditability
• Partner across teams to establish clear ownership of marketing data assets and definitions

Collaboration & Delivery

• Partner with Marketing, Customer First, and Analytics teams to translate business needs into scalable data solutions
• Support self-service analytics by building intuitive, reusable datasets across channels (e.g., digital, lifecycle, events)
• Contribute to scalable data workflows that balance immediate campaign needs with long-term maintainability
• Work within an agile environment, contributing to planning, prioritization, and continuous improvement

AI and Data Mindset

• Demonstrate an AI-first mindset, thinking beyond data models and dashboards to how data can power intelligent systems and decision-making
• Understand the importance of well-modeled, well-documented, and semantically clear data for AI and LLM-based use cases
• A level of comfort leveraging AI-assisted workflows to improve productivity, code quality, and consistency
• Curiosity for emerging capabilities in platforms like Snowflake Cortex and Snowflake Intelligence, and how they can be applied to Marketing analytics

What you’ll bring to the role

• 5–8+ years of experience in Analytics Engineering, Data Engineering, or similar roles
• Strong SQL skills and experience building analytics-ready data models
• Mentorship & Engineering Excellence: Mentorship, raising the technical bar, establishing organization-wide standards for dbt/SQL quality and CI/CD
• Hands-on experience with dbt and Snowflake or other ETL, Modeling and database platforms
• Solid understanding of data modeling principles, including dimensional modeling and semantic design
• Experience working with Marketing data (e.g., campaign data, web analytics, CRM, attribution models)
• Familiarity with tools such as Salesforce, Marketo, Google Analytics, or similar platforms
• Experience with data quality, testing, and documentation best practices
• Exposure to Python, R, or data processing frameworks (e.g., PySpark) is a plus
• Experience with BI tools such as Tableau or Looker
• Strong communication skills and ability to work across technical and business teams

What you can look forward to as an Okta employee!

• Amazing Benefits
• Making Social Impact
• Fostering Diversity, Equity, Inclusion and Belonging at Okta 
• Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/. 

Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/.

#LI-HM2

#LI-Hybrid

P24712_3413650

P24715_3413656

The Pricing Strategy Team
Okta’s Pricing Strategy team partners across Product, Finance, Sales, and Operations to shape how we package, price, and monetize our portfolio globally. We sit at the intersection of strategy and analytics, translating market signals and customer behavior into clear recommendations that drive growth and value capture. The team’s work is highly cross-functional and directly influences executive decision-making and field execution.

The Principal Data Scientist, Pricing Strategy Opportunity
Reporting to the Head of Pricing Strategy, this role will lead the data science and analytics strategy that underpins portfolio-level pricing and packaging decisions. You’ll combine strong quantitative rigor with strategic thinking to design measurement approaches, build and operationalize models, and run test-and-learn pilots that inform high-impact monetization programs. You will partner closely with senior leaders across Product and GTM to turn ambiguous questions into actionable insights, recommendations, and scalable execution plans.

What you’ll be doing

• Strategic Pricing Influence: Partner with Product, GTM, and Finance leadership to inform portfolio-level pricing, packaging, and discount strategy with data-driven recommendations
• Advanced Analytics and Modeling: Build and operationalize models and analytical frameworks to forecast pricing impact, customer behavior, and revenue outcomes across segments and geographies
• Experimentation and Pilots: Design and evaluate pilots and test-and-learn programs for new pricing initiatives, defining success criteria and measurement plans
• Deep-Dive Insight Generation: Analyze large, complex datasets to uncover drivers of purchasing, discounting, retention, and monetization performance
• Metrics and Dashboard Development: Establish the right KPIs and build dashboards to monitor monetization strategy effectiveness and the ROI of pricing initiatives in real time
• Data Foundation Partnership: Work with Okta Data teams to shape and enhance the foundational data required for pricing analytics initiatives
• Cross-Functional Execution Partnership: Translate strategy and insights into operational requirements, working with stakeholders across Sales, Legal, and Systems teams to enable implementation and adoption

What you’ll bring to the role

• 8+ years of experience in data science, analytics, pricing, strategy consulting, or a related quantitative field (B2B SaaS preferred)
• Proven ability to apply statistical rigor and structured analytics to ambiguous business problems and deliver measurable impact
• Experience designing measurement approaches for business initiatives (e.g., pilots, rollouts, test-and-learn), and communicating results with clarity
• Strong proficiency in SQL and Python, with experience working in modern data environments (e.g., Snowflake) and BI tools (e.g., Tableau)
• Ability to synthesize complex data using quantitative approaches, translate findings into clear visualizations, and deliver executive-ready insights and recommendations
• Demonstrated ability to influence cross-functional senior stakeholders and lead through ambiguity with strong collaboration and ownership

And extra credit if you have experience in any of the following!

• Experience in pricing, packaging, monetization, or growth strategy for multi-product SaaS portfolios
• Familiarity with forecasting, optimization, or causal measurement methods in a business context
• Experience partnering with Sales/GTM teams to drive adoption of new programs and measure field impact

#LI-MC1

#LI-Hybrid

#P17449_3411893

The Field Analytics Team

As part of Okta’s Go-To-Market Strategy & Operations group, the Field Analytics team is the primary engine for strategic analysis, enabling our leaders to make evidence-based decisions that determine the trajectory of Okta’s growth.

Manager, Field Analytics Opportunity

We are looking for a Manager, Field Analytics to serve as a strategic partner of our Solutions Engineering and Partner organizations. You will transform complex data into actionable strategies, identifying key revenue drivers and building scalable analytical frameworks that directly influence Okta's strategic direction.

You will act as the primary liaison between our data infrastructure and our most technical go-to-market branches. Your mission is to build scalable, flexible reporting that drives proactive insights that optimize technical sales productivity and accelerate partner-led growth while championing the adoption of emerging AI capabilities. 

Impact & Responsibilities:

• Strategic Partnership: Act as a dedicated analytics lead for the Pre-Sales and Partners operations and leadership teams. Develop deep relationships to understand their business rhythms and operational needs, translating complex business questions into analytical frameworks.
• AI Readiness & Innovation: Lead the "AI readiness" initiative for field data. This includes exploring AI solutions to help pre-sales and partner teams drive growth, document processes, and brainstorm innovative ways to use AI tools for internal productivity.
• Analytics Delivery: Design, build, and maintain high-visibility Tableau dashboards and reporting assets. You will work in close partnership with our offshore delivery team to progress work faster and scale foundation reporting while you focus on high-complexity strategic projects.

Required Skills & Qualifications: 

• 6+ years in an operational and analytical capacity (Sales Operations, Business Intelligence, or Revenue Analytics), preferably within a fast-paced SaaS environment.
• Expert-level proficiency in SQL (Snowflake), BI Visualization tools (Tableau), and CRM data (Salesforce).
• Proven ability to build advanced analytical models (e.g., productivity modeling, variance analysis) and high-visibility dashboards.
• Ability to look beyond the "what" to the "why" and "so what," providing actionable recommendations that change business behavior.
• Exceptional written and verbal communication skills, with a proven ability to distill complex technical findings into strategic narratives for senior executives.
• A relentless curiosity and a desire to "build it and own it," working both independently and collaboratively across a global delivery model.

Preferred Qualifications: 

• Track record of experimenting with AI tools (e.g., Gemini, ChatGPT, Claude Code) or implementing AI-based workflows to optimize data modeling and automate documentation.
• Proficiency with scripting languages (Python) and modern data modeling frameworks (dbt).
• Prior experience supporting a Solutions Engineering or Partner/Channel organization.
• Experience in SaaS GTM.

#LI-MC1

#LI-Hybrid

#P5992_3420266

About the Role

As a member of our technical support engineering team, you will be on the front lines providing world-class customer service. As part of our engineering organization, you will become an expert on our product and partner closely with Metronome's engineers, customer success, solutions architecture, and growth teams, as well as our customers' developers.

Your primary responsibilities will include handling customer escalations through our ticketing system, using internal observability tools to diagnose and scope customer-facing issues, collaborating directly with customers via Slack and other channels, and developing internal tools and documentation to improve the support experience. Since we view every support escalation as an opportunity to learn, both as individuals and as a company, you will play a critical role in providing feedback to our product team on common challenges and influencing our product roadmap.

What You'll Do

• Provide technical guidance to customers’ developers on best practices for integrating with our APIs and utilizing our functionality.
• Troubleshoot any issues that arise from customers and diagnose any blockers. Escalate issues with customer context to the engineering team.
• Develop internal tools to automate customer workflows that are currently unavailable in our product. Provide feedback on recurring patterns and advocate for addressing feature gaps in the product.
• Design and assist in implementing a comprehensive knowledge base to assist customers with using our product.

Impact You'll Have

• Through your interactions with individual customers, you will help improve our product for everyone.
• Your work will play a crucial role in ensuring our customers' success and the continued effectiveness of their integration with Metronome.
• The Metronome team is more well-rounded because you bring your unique personality to work and help create an inclusive fun environment focused on helping our customers get the most value out of Metronome.

Qualifications

• 2+ years of work experience in a B2B customer-facing technical support organization or in engineering
• Experience working closely with engineering teams and providing technical feedback on customer issues
• Ability to debug and triage bugs and escalations from customers
• Can communicate technical capabilities of the product to customers
• Experience writing scripts or internal tools using APIs, and functional knowledge of SQL
• Strong written and verbal communication skills, with the ability to break down complex technical concepts clearly
• A mindset of customer empathy and ability to solve challenging problems

Bonus points

• Experience as an early or founding member of a support team, including building processes from scratch
• Startup experience and familiarity with scaling a support team
• Programming experience in one or more of Typescript, Python, or Ruby
• You have worked on modern enterprise software which is business critical
• Experience creating knowledge base articles and internal documentation
• Familiarity with at least one ticketing system, such as Pylon, Zendesk, Front, or similar

Compensation

The estimated base salary range for this role is $137,000 - $205,600. In addition to your base salary, Metronome offers a competitive total rewards package, including but not limited to, market-benched equity, sales incentive pay (for eligible roles), comprehensive health benefits, and other benefits listed below.

The actual base salary will vary based on factors including market value, individual qualifications objectively assessed during the interview process, and previous experience. The listed range above should serve as a guideline and may be modified at any time.

We believe that compensation reflects the expected impact you will have at the company, relative to the market value of your role. We also conduct an annual pay audit to ensure pay is fair, indexed to market value, and that pay takes into account continued performance at Metronome. If you would like to learn more about our philosophy or about why we are all billing nerds, send us a message. We’d love to talk!

About this role:

The Corporate Security team at Faire owns the tools and policies that keep our people, data, and systems protected. The team's scope includes endpoint detection, data loss prevention, email security, corporate threat detection, compliance training, and AI governance. As our Staff Engineer focusing on Enterprise AI, you will be Security and IT's technical leader for AI systems, partnering with engineering teams in driving AI initiatives to ensure governance, security, and enablement scale alongside adoption. You'll work across every level of the organization, balancing the drive to "Make it happen fast" with the discipline to move safely.

What you'll do:

• Own and drive Faire's company-wide AI strategy in partnership with engineering, business, and executive stakeholders. This means setting the direction for which tools we adopt, how we govern them, and how we scale adoption.
• Serve as the technical authority on AI platform administration for tools like Anthropic and OpenAI. You'll evaluate, enable, and disable native connectors, plugins, and features based on risk, security posture, and business value.
• Build and maintain decision frameworks (e.g., risk matrices, enablement criteria) that make AI governance repeatable and transparent.
• Design and engineer secure experimentation infrastructure, including sandboxed environments, isolated MCP connectors for testing new features, and scoped OAuth flows, so teams can safely explore new AI capabilities.
• Design and build custom MCP integrations when out-of-the-box options don't exist or don't meet Faire's security requirements (e.g., overly broad permissions, insufficient audit logging).
• Lead AI pilot programs end-to-end, from scoping and stakeholder alignment through rollout, troubleshooting, feedback collection, and iteration.
• Engineer observability and compliance infrastructure, ensuring compliance logs from AI platforms end up in our SIEM.
• Own the operational mechanics of AI adoption tracking. This includes automating usage data pipelines into Snowflake and partnering with data analysts and domain teams (engineering, CX, etc.) who own their respective adoption metrics.
• Partner with Learning & Development and engineering teams to build and deliver AI training, prompt libraries, and enablement resources tailored to different roles and workflows.
• Embed with teams across the company to understand their workflows, identify where AI can accelerate their work, and just as importantly, where it shouldn't be used.
• Communicate AI strategy, risk trade-offs, and recommendations clearly to audiences ranging from junior engineers to C-level executives, including respectfully challenging perspectives when the data warrants it.
• Stay current with the rapidly evolving AI product landscape and proactively assess new capabilities (e.g., new platform features, agent frameworks) for security implications and business value.

What it takes:

• 7+ years of experience in security engineering, platform engineering, infrastructure engineering, or IT engineering.
• Experience building and presenting decision frameworks, risk assessments, or strategy recommendations to senior leadership.
• Ability to operate independently, setting your own strategy, building stakeholder relationships, and executing with minimal oversight.
• Strong communication skills across a wide range of audiences, from mentoring junior engineers to partnering with executives in strategy discussions.
• Proficiency in at least one object-oriented programming language (e.g., Python, Go, Ruby, Java) with the ability to build integrations, tooling, and automations from scratch.
• Hands-on experience administering or deeply integrating with AI/LLM platforms. Not just using them, but managing them at the platform level (e.g., building MCP servers, extending LLM functionality, managing enterprise AI admin consoles).
• Experience designing scalable internal systems and infrastructure. You think about solving categories of problems at the platform level, not building one-off solutions.
• Track record of owning company-wide programs that delivered measurable impact to downstream users or the business.
• Experience with observability or SIEM tooling (e.g., Datadog, Splunk) and building data pipelines for monitoring and compliance.

Nice to have:

• Understanding of LLM internals, including transformer architectures, tokenization, context window management, RAG patterns, prompt engineering techniques, and the security risks inherent to each (e.g., prompt injection, data leakage through context, output manipulation).
• Prior experience in an AI governance, AI enablement, or AI strategy role.
• Experience with observability or SIEM tooling (e.g., Datadog, Splunk) and building data pipelines for monitoring and compliance.
• Familiarity with security and compliance considerations specific to AI tooling, such as data residency, DLP policies for AI-generated content, agent access controls, and OAuth scoping for third-party integrations.
• Experience building internal enablement programs, whether training courses, documentation, or developer advocacy, that drove measurable adoption of new tools or practices.

Salary Range:

San Francisco: the pay range for this role is $204,000 - $280,500 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About the Role

The Revenue Operations team at Gusto is a full-stack team responsible for data, analytics, and operational excellence in pursuit of scaling our revenue growth. The Go-To-Market Analytics team is one functional area, responsible for defining and owning the metrics for scaling our Sales teams. 

Gusto is looking for a Revenue Analytics Engineer to build and maintain foundational data infrastructure that is crucial to growing and scaling our Sales efforts. In this role, you will partner with our GTM analysts to scope and deliver data products for an audience ranging from company and revenue leadership to operational and frontline sales. In doing so, you will own significant portions of our sales data from end-to-end, focusing on the transformation, design, and visualization workflows. In addition, you will establish best practices for systems design and workflows to maximize usefulness of AI at scale. 

This role will report to the Head of Go-To-Market analytics, and partner closely with Data Science, Data Platform, and Business Technology teams. 

Here’s what you’ll do day-to-day:

• Establish relationships with internal stakeholders to determine business needs, scoping and delivering solutions through data products
• Design, build, and maintain data pipelines and dashboards to automate “keep the lights on” work out of manually-managed processes
• Build a data foundation by incorporating business logic into raw data tables, laying the groundwork to enable value-add insights
• Create a dynamic reporting environment based on stakeholder needs
• Identify data discrepancies and set best practices for data logic to create a clean and well-documented environment
• Collaborate with broader data organization as steward to the definition and process management of core Gusto metrics

Here’s what we're looking for:

• Education or work experience in Engineering or Computer Science, or a related technical field 
• 7+ years of experience in an analytics engineering, business intelligence, or technical data analytics role
• Experience with SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, Snowflake, etc.
• Command-line experience and familiarity with version control collaboration tools (git)
• Experience with data pipeline management technologies with dependency checking, such as Airflow, as well as schema design and data modeling tools (dbt)
• Experience with data visualization technologies, e.g., Tableau, Looker, Sigma, Mode, Hex
• Experience with Python and data ingestion tools
• Ability to problem-solve open-ended problems and project manage dependencies and timelines to optimal outcomes
• Ability to demonstrate tools, business intuition, and attention to detail for data validation and QA 

Our cash compensation amount for this role is targeted at $138,000-156,000 in Denver & most remote locations, and $168,000-189,000 in New York & San Francisco Bay Area. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

The Data Engineering team builds tools and systems that make Gusto's data consistent, user-friendly, and helpful. This helps our teams make decisions using data and provide intelligent, customized experiences to our customers.

We're looking for a Senior Data Engineer who can take loosely defined problems and drive them end-to-end—from framing the problem and aligning stakeholders to designing, building, and delivering durable data solutions. You’ll partner closely with analytics, product, and engineering teams to deliver data solutions that drive real business and customer impact.

Preferred Qualifications

• 8-10+ years of industry experience in data engineering building scalable data pipelines and data products
• Strong proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
• Proven experience building and maintaining robust data pipelines and ETL workflows, with hands-on dbt experience for reliable, testable, and maintainable data transformations.
• Hands-on experience ingesting data from diverse sources, including APIs, databases, SaaS applications, and event streams.
• Strong foundation in data modeling, schema design, and data quality best practices, with functional experience working on cloud platforms like Snowflake, Redshift, BigQuery, or Databricks.
• Experience implementing CI/CD pipelines, automated testing, and data observability to ensure reliability and trust in data systems
• Familiarity with monitoring, alerting, and incident response for production-grade data pipelines
• Proven ability to optimize performance and cost across data workflows and storage systems
• Functional understanding of how to leverage AI and automation in data engineering — building self-service tools, intelligent pipelines, and agents that automate repetitive tasks
• Exemplar problem-solving skills and ability to work collaboratively in cross-functional teams.
• Strong communication and collaboration skills, with a focus on clarity, empathy, and shared ownership

Compensation Details

Our cash compensation amount for this role is targeted at $155,000-$185,000/yr in Denver, $170,000-$200,000/yr in Los Angeles, and $190,000-$220,000/yr for San Francisco, Seattle, and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

Flex is looking for a Staff level Engineer to join our dynamic team and play a pivotal role in accelerating our growth trajectory. In this role, you will be instrumental in developing and scaling the platform and app experiences that empower our users and partners, unlocking our next phase of 10x growth.

What You'll Do:

• Focus on creating exceptional user and partner experiences that drive engagement and retention.
• Partner closely with product managers, designers, and data scientists, data analysts to identify and solve critical user onboarding challenges.
• Design, develop, test, and deploy robust APIs, services and data pipelines that enhance user onboarding and overall platform experience.
• Implement changes through an agile methodology, prioritizing rapid iteration and continuous improvement.
• Utilize data and analytics to measure the impact of your work and identify opportunities for optimization.

Qualifications

Minimum Qualifications

• 7+ years of professional software development experience.
• 3+ years of hands-on experience with Java.
• 3+ years of experience with React or React Native.
• 3+ years of experience with TypeScript.
• Having experience building high-quality mobile and web UIs to specifications is a must to have.
• Proficient in Java frameworks and tools used at Flex, including Spring (core/web/boot), Gradle, JUnit, and JVM (memory/performance tuning, GC).
• Experience with Service-Oriented Architecture, REST APIs, Message Queues, and scalable architectures.
• Experience with architectures and tools in React Native and React ecosystems (Hooks, Components, Context, Redux).
• Experience with AWS (EKS, Aurora RDS, Elasticache, DynamoDB) and containerization tools.

Preferred Qualifications

• Have the experience to build and improve user onboarding funnel and design the comprehensive experiment to drive metric improvements.
• Proficient in CI/CD systems (preferably GitHub Actions), git, and automation.
• Skilled in observability and monitoring tools, such as DataDog, to ensure high availability.
• Experienced with big data platforms and tooling, including Snowflake.
• Proficient in Infrastructure as Code, using tools like CDK and Terraform.
• Skilled at elevating team standards through best practices, and mentoring junior engineers.
• Excellent written and verbal communicator, with experience in cross-functional collaboration.

• Tier A (NYC/SF/Seattle): $200,000—$250,000 USD
• Tier B: $180,000—$225,000 USD
• Tier C: $170,000—$212,000 USD

About the role

Flex is looking for a Senior Software Engineer to join our Risk Engineering team. This role involves spearheading the implementation of platforms and APIs crucial for supporting business features within the risk management domain.

The Risk Engineering team is dedicated to mitigating both credit risk, fraud risk, and risk for launching new products. Our mission is to enhance Flex app accessibility for customers while safeguarding against improper use and unauthorized access by identifying and preventing misuse across all core product areas.

Following are some projects/systems in Risk Platform you will have opportunities to work with:

• Core decision platform which is an end-to-end solution for the enterprise decision management lifecycle, including business rule management, analytics, process management, and ML/AI.
• Event data stream ingestion which supports near real-time fraud rules setup. 
• Advanced a/b testing and experimentation capabilities for our customers so they can leverage greedy algorithms and fight fraud. 

What You'll Do:

• Build decision platform / machine learning solutions to respond to/mitigate business risks in Flex.
• Design and develop 24/7 high-scale APIs and distributed systems. The tech stack will be on AWS. Java would be the language for the existing code base. Java Spring Boot will be the framework. 
• Work closely with product, design, and engineering peers to launch new features across our web and mobile platforms 

Qualifications

Minimum Qualifications

• Must-have: Experience working in a risk engineering team, specializing in rules engine architecture or risk/credit/fraud systems.
• 6+ years of professional software development experience.
• 5+ years of hands-on experience with Java.
• 2+ years of experience with React or React Native.
• 2+ years of experience with TypeScript.
• Having experience building high-quality mobile and web UIs to specifications is a must to have.
• Proficient in Java frameworks and tools used at Flex, including Spring (core/web/boot), Gradle, JUnit, and JVM (memory/performance tuning, GC).
• Experience with Service-Oriented Architecture, REST APIs, Message Queues, and scalable architectures.
• Experience with architectures and tools in React Native and React ecosystems (Hooks, Components, Context, Redux).
• Experience with AWS (EKS, Aurora RDS, Elasticache, DynamoDB) and containerization tools.

Preferred Qualifications

• Proficient in CI/CD systems (preferably GitHub Actions), git, and automation.
• Skilled in observability and monitoring tools, such as DataDog, to ensure high availability.
• Experienced with big data platforms and tooling, including Snowflake.
• Proficient in Infrastructure as Code, using tools like CDK and Terraform.
• Skilled at elevating team standards through best practices, and mentoring junior engineers.
• Excellent written and verbal communicator, with experience in cross-functional collabo

• Tier A (NYC/SF/Seattle): $172,000—$210,000 USD
• Tier B: $154,000—$190,000 USD
• Tier C: $146,000—$180,000 USD

Flex is looking for an Engineer to join our dynamic team and play a pivotal role in accelerating our growth trajectory. In this role, you will be instrumental in developing and scaling the platform and app experiences that empower our users and partners, unlocking our next phase of 10x growth.

What You'll Do:

• Focus on creating exceptional user and partner experiences that drive engagement and retention.
• Partner closely with product managers, designers, and data scientists, data analysts to identify and solve critical user onboarding challenges.
• Design, develop, test, and deploy robust APIs, services and data pipelines that enhance user onboarding and overall platform experience.
• Implement changes through an agile methodology, prioritizing rapid iteration and continuous improvement.
• Utilize data and analytics to measure the impact of your work and identify opportunities for optimization.

Qualifications

Minimum Qualifications

• 5+ years of professional software development experience.
• 3+ years of hands-on experience with Java.
• 3+ years of experience with React or React Native.
• 3+ years of experience with TypeScript.
• Having experience building high-quality mobile and web UIs to specifications is a must to have.
• Proficient in Java frameworks and tools used at Flex, including Spring (core/web/boot), Gradle, JUnit, and JVM (memory/performance tuning, GC).
• Experience with Service-Oriented Architecture, REST APIs, Message Queues, and scalable architectures.
• Experience with architectures and tools in React Native and React ecosystems (Hooks, Components, Context, Redux).
• Experience with AWS (EKS, Aurora RDS, Elasticache, DynamoDB) and containerization tools.

Preferred Qualifications

• Have the experience to build and improve user onboarding funnel and design the comprehensive experiment to drive metric improvements.
• Proficient in CI/CD systems (preferably GitHub Actions), git, and automation.
• Skilled in observability and monitoring tools, such as DataDog, to ensure high availability.
• Experienced with big data platforms and tooling, including Snowflake.
• Proficient in Infrastructure as Code, using tools like CDK and Terraform.
• Skilled at elevating team standards through best practices, and mentoring junior engineers.
• Excellent written and verbal communicator, with experience in cross-functional collaboration.

• Tier A (NYC/SF/Seattle): $172,000—$210,000 USD
• Tier B: $154,000—$190,000 USD
• Tier C: $146,000—$180,000 USD

About the job

Flex is hiring Senior Software Engineer, Backend roles across four engineering teams: Consumer, Partner Integrations, Core Platform, and Risk. When you apply, you will automatically be considered for all open Senior Backend positions, and your placement will be determined based on your experience and expertise assessed during the interview process.

As a Senior Backend Engineer at Flex, you will play a key role in designing, building, and scaling backend services and APIs that power our products, partner integrations, and critical risk management platforms. You’ll collaborate closely with cross-functional teams to deliver robust, fault-tolerant systems that impact renters and partners at scale.

You will own the end-to-end lifecycle of your services- from requirements and architecture through implementation, testing, deployment, and monitoring- and help elevate the team by driving technical best practices and mentoring junior engineers.

Our Engineering Teams

• Consumer Engineering: Builds the APIs and backend systems powering Flex’s main consumer-facing products. This team focuses on delivering scalable services for a seamless rent payment experience through our mobile and web apps.
  
  
• Partner Integrations Engineering: Owns the backend services and integrations that connect Flex to financial partners and payment networks, ensuring reliable, secure payment flows and partner-facing experiences.
  
  
• Core Platform Engineering: Maintains the backend systems and infrastructure supporting all business features, including Payments, Billing, Identity, and Partner Integrations, ensuring Flex’s foundation is robust and scalable.
  
  
• Risk Platform Engineering: Develops the platforms and APIs that mitigate credit and fraud risk, enhancing customer accessibility while safeguarding against misuse through advanced rules engines, machine learning, and event data systems.

A minimum of 4 years of experience with Java is required for this position.

What You'll Do

• Design, develop, test, and scale backend services and APIs that power Flex’s consumer products, partner integrations, risk management systems, and core platform services.
• Build and operate robust, fault-tolerant distributed systems with multiple external dependencies.
• Implement service APIs for web and mobile apps, simplifying complex rent payment processing.
• Work closely with Product, Design, Infrastructure, Sales, Partner, and Customer Success to deliver features and integrations that delight customers and partners.
• Translate feature requirements into technical specifications and lead the architecture and implementation of scalable solutions.
• Drive the full lifecycle of services and APIs you build, including deployment, monitoring, and optimization for high availability and performance.
• Contribute to evolving Flex’s service-oriented architecture, REST APIs, message queues, and scalable systems design.
• Develop risk management systems such as rules engines, ML-powered fraud detection, and high-scale event ingestion pipelines.
• Mentor junior engineers and help elevate the team’s engineering practices through code reviews, architecture discussions, and technical leadership.
• Ensure services are observable and reliable using monitoring tools and industry best practices.
• Collaborate on CI/CD improvements and automation to increase code quality and delivery velocity.

Key Qualifications

• • Strong computer science fundamentals with a proven track record of building scalable backend systems.
  • 5–6+ years of professional software engineering experience with a focus on backend development.
  • 4+ years of hands-on Java experience, with deep knowledge of the Java ecosystem.
  • Proficient in Java frameworks and tools used at Flex: Spring (core/web/boot), Gradle, JUnit, JVM tuning and performance optimization.
  • Experience operating services in distributed, service-oriented architectures at scale.
  • Familiarity with REST API design, mobile API best practices, and message-driven architectures.
  • Skilled at building robust, fault-tolerant systems and integrating with multiple external dependencies.
  • Experience designing and maintaining data pipelines and working with big data platforms (bonus: Snowflake).
  • Hands-on experience with AWS (EKS, Aurora RDS, Elasticache, DynamoDB), containerization (Docker/Kubernetes), and Infrastructure as Code (CDK/Terraform).
  • Skilled in observability and monitoring tools (e.g., DataDog) to ensure high availability.
  • Ability to write high-quality code that is testable, maintainable, scalable, and secure, using industry best practices throughout the SDLC (unit testing, build automation, CI/CD).
  • Excellent communicator, comfortable working with distributed teams and cross-functional stakeholders.
  • Proven ability to mentor junior engineers and raise the technical bar through best practices.
  Risk Platform candidates: Experience in risk engineering, rules engine architecture, and implementing risk/fraud/credit policies in production systems is highly valued.

• Tier A: (NYC/SF): $172,000 —$215,000 USD
• Tier B: $154,800—$193,500 USD
• Tier C: $146,200 —$182,750 USD

#LI-Remote

The Role

Analytics Engineering at Flex sits at the intersection of Data, Product, Engineering, and business objectives. As Director, Analytics Engineering you will run the team that enables stakeholders at Flex to easily find the data they need to make decisions. You’ll be responsible for developing a world-class analytics platform that powers all data consumption at Flex, as well as managing and developing a team of high-performing Analytics Engineers. You'll also be hands-on, leveraging your technical skills to develop data models and build better data products and solutions. You'll partner with analysts, engineers, PMs and others to define the requirements while being accountable for delivering the end data product.

You Will:

• Develop and lead strategy for data modeling platform and team roadmap
• Manage and mentor a team of Analytics Engineers
• Collaborate with leaders across product & engineering teams to define data requirements and inform architecture/schema design decisions
• Lead the development of data models to consume, transform, and expose data to stakeholders and systems across the company
• Collect business requirements, define successful analytics outcomes, and design data solutions
• Set company-wide standards for data regarding structure, quality, and expectations
• Contribute Flex’s data culture by influencing processes, systems, and tools that enable to make better decisions in a scalable way

You Have:

• 8+ years as an analytics engineer or equivalent, with a track record of shipping high quality products and features at scale
• Expert knowledge of SQL, data warehouses (we use Snowflake), and how to write efficient SQL queries
• Familiarity with common BI tools (preferably Sigma Computing, Tableau, Mode, etc.)
• Expert proficiency with dbt, dbt Cloud, and Airflow
• Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, and best practices for codebase development and CI/CD)
• Proficiency with Python preferred
• Experience within the fintech space preferred

Flex takes a market-based approach to pay, and compensation may vary depending on your primary work location. Work locations are categorized into one of three tiers based on a cost of labor index for that geographic area.  

Tier A (NYC/SF/Seattle): $240,000-290,000
Tier B (Austin, Washington D.C. Philadelphia, Los Angeles, San Diego, Chicago, Miami, Atlanta : $215,000-265,000
Tier C (SLC/All Other States): $200,000-250,000

Offices

Roles posted in New York, San Francisco, or Salt Lake City are hybrid positions with on-site expectations of 2-3 days per week in our local offices. For candidates outside of these areas, you may be eligible for our relocation assistance program.

As one of our Senior Data Analysts of our Global Data team, you will work closely with the expense team and stakeholders from across the business including engineers, sales, marketing, finance, and operations to define the data needs and products which will drive the business forward. The ideal candidate will be extremely curious, independent, knowledgeable about data, and will use their data skills and business mindset to make a difference every day. We are looking for people who can operate at a company that grows as fast as ours by dealing with multiple moving pieces while still holding up quality, long-term thinking, and delivering value to our customers. We take great pride in our diversity of backgrounds, cultures, and perspectives and we strongly believe this is helping us to grow as a successful and impactful team. 

What You'll Do

• Identify trends and opportunities for growth through analysis of complex data sets
• Work alongside stakeholders (from ICs/Engineers to Directors/E-Staff) to understand requests and provide solutions using data analytics
• Provide data solutions end-to-end (working with raw data, developing SQL models, building dashboards and presenting insights to stakeholders)
• Support and strengthen our fast paced fintech product team in all functional areas and special requests as needed
• Create and deliver documentation and training on reporting and BI tools for business users to enable self-service on company data
• Consolidate data across business units and acquisitions with different definitions and measurement. 
• Ongoing commitment to identify and implement process improvements for operational efficiencies and enhanced analytics as well as maintain existing documentation of control procedures performed by the financial planning and analysis team
• Develop SQL models using data warehousing principles (we use dbt).

What We're Looking For

• Preferred Bachelor’s degree or equivalent experience
• Over 5 years of professional experience in the field of Data Analysis
• Proficiency with Data Visualization Tools for at least 2 years
• Strong command of SQL
• Prior experience in fintech is a big plus
• Ability to effectively interpret business requirements and translate them into analytical solutions, insights, and reports
• Proficient in standard statistical techniques such as significance testing and regression modeling
• Demonstrated eagerness to acquire new technological skills and problem-solving abilities
• Familiarity with Snowflake and dbt is beneficial
• Excellent communication skills and adept at building relationships with stakeholders; must also be a collaborative team player

What You’ll Do:

The Data Services Team builds and operates the data platform that powers CoreWeave's AI cloud, from transactional and analytical storage to streaming, metadata, and governance. We give our customers and CoreWeave engineers the primitives they need to ingest, store, process, and serve data at the scale and performance that next-generation AI workloads demand.

If you want to define how data flows across a rapidly scaling AI cloud, and turn that strategy into infrastructure others depend on, this is your team.

About the role:

As a Staff Product Manager for Data Services, you'll own the end-to-end strategy, roadmap, and execution for CoreWeave's data services portfolio: databases, data lakes, streaming, metadata and catalog, and data sharing and integration.

You'll shape a multi-year vision for how our data services underpin AI and GPU workloads, then lead delivery from 0 to 1 and 1 toN. That means working directly with strategic customers and partners, collaborating closely with engineering and GTM, evaluating emerging data technologies, and ensuring our services are secure, reliable, and easy to adopt.

The hardest problems you'll tackle are around scale, throughput, and performance for GPU-intensive applications, and you'll have real influence over the architecture to solve them.

In this role, you will own:

• Product strategy and roadmap across the data services portfolio, balancing near-term delivery with long-term bets
• Customer and partner engagement - diving deep into data architectures, co-designing solutions, and supporting large-scale deployments
• Cross-functional alignment with engineering, GTM, and leadership to drive clarity and execution in a fast-moving environment
• Market and competitive analysis to surface opportunities, validate priorities, and keep us ahead of the curve
• API-first platform thinking - partnering with architects on service designs, SLAs, and operational excellence

Who You Are: 

• 8+ years of product management experience in data platforms, databases, analytics, or cloud infrastructure, with at least 3-4 years focused on data services (managed databases, streaming, data warehouses, data lakes, or governance platforms)
• Technical fluency in:
• Relational and/or distributed databases (e.g., PostgreSQL, MySQL, SingleStore, Snowflake, BigQuery)
• Streaming and pipelines (e.g., Kafka, CDC, ETL/ELT, lakehouse architectures, real-time data sharing)
• Data security and governance (encryption, IAM/RBAC, data masking, network isolation, compliance)
• A track record of owning complex, API-first platform products from concept through multiple release cycles
• Strong communication skills - able to create clarity from ambiguity, influence without authority, and translate technical depth for any audience
• Comfort operating in a fast-paced, high-growth environment where the answer isn't always obvious

Preferred:

• Staff or Director-level PM experience at a database vendor, cloud provider, or high-growth infrastructure company
• Hands-on experience with managed data services on AWS, Azure, or GCP (e.g., RDS, Aurora, Cosmos DB, BigQuery)
• Background in hybrid or multi-cloud architectures: connectivity, data locality, replication
• Experience with AI/ML data products: feature stores, vector search, real-time analytics, or serving pipelines for LLM workloads
• Familiarity with SaaS/PaaS packaging and usage-based or tiered pricing models
• Prior engineering or architecture experience on data or distributed systems

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• Love building platforms that other teams and customers treat as critical infrastructure
• Are curious about new databases, analytics, and AI data patterns, and are good at separating real value from hype
• Can drive clarity in highly technical, ambiguous problem spaces and rally cross-functional teams around a plan
• Enjoy going deep with customers on their data architectures and co-designing solutions
• Balance long-term vision with fast iteration, and you don't need perfect information to move forward

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

CoreWeave, the AI Hyperscaler™, acquired Weights & Biases to create the most powerful end-to-end platform to develop, deploy, and iterate AI faster. Since 2017, CoreWeave has operated a growing footprint of data centers covering every region of the US and across Europe, and was ranked as one of the TIME100 most influential companies of 2024. By bringing together CoreWeave’s industry-leading cloud infrastructure with the best-in-class tools AI practitioners know and love from Weights & Biases, we’re setting a new standard for how AI is built, trained, and scaled.

The integration of our teams and technologies is accelerating our shared mission: to empower developers with the tools and infrastructure they need to push the boundaries of what AI can do. From experiment tracking and model optimization to high-performance training clusters, agent building, and inference at scale, we’re combining forces to serve the full AI lifecycle — all in one seamless platform.

Weights & Biases has long been trusted by over 1,500 organizations — including Nvidia, Canva, Cohere, Meta, Snowflake, Square, Toyota, and Amazon — to build better models, AI agents and applications. Now, as part of CoreWeave, that impact is amplified across a broader ecosystem of AI innovators, researchers, and enterprises.

As we unite under one vision, we’re looking for bold thinkers and agile builders who are excited to shape the future of AI alongside us. If you're passionate about solving complex problems at the intersection of software, hardware, and AI, there's never been a more exciting time to join our team.

About the Role:

As an AI Solutions Engineer you will sit at the intersection of cutting-edge AI infrastructure and the world’s most ambitious AI teams. You will help customers design, deploy, and scale modern ML and GenAI systems using Weights & Biases and CoreWeave’s AI cloud. This role combines hands-on technical depth with strategic customer engagement — ideal for AI practitioners who enjoy building real systems, solving complex problems, and shaping how AI is developed and operationalized at scale.

What You’ll Do:

• Own the technical wins by building proof of value (PoVs). You’ll be partnering with Account Executives to drive discovery, solution design, and successful technical evaluations.
• Lead deep technical conversations with ML engineers, researchers, and platform teams to understand their AI/GenAI workloads and architect scalable solutions across the CoreWeave and Weights & Biases ecosystem .
• Design and deliver compelling live demos, proof-of-value engagements, and rapid prototypes showcasing experiment tracking, distributed training, agentic workflows, fine-tuning, evaluation, and inference at scale.
• Architect modern ML and GenAI systems including distributed training, RAG pipelines, multi-agent systems, LLM fine-tuning workflows, and inference solutions.
• Translate business objectives into measurable technical outcomes such as model quality improvements, cost reductions, performance gains, and faster iteration cycles.
• Serve as a trusted technical advisor, influencing architectural decisions and best practices across MLOps, LLMOps, and platform engineering.
• Partner closely with Product and Engineering to relay customer feedback, shape roadmap priorities, and improve the end-to-end AI developer experience.

Who You Are:

• 2+ years of experience in Solutions Engineering, ML Engineering, AI Engineering, or a similar customer-facing technical role.
• Bachelors degree in Computer Science, Data Science, Electrical Engineering, Statistics, Mathematics, or related field. Master in similar area of study preferred.
• Strong proficiency in Python (bonus: TypeScript/JavaScript) and experience building production-grade ML or GenAI applications.
• Hands-on experience training, fine-tuning, evaluating, debugging, and deploying deep learning or LLM-based systems.
• Experience with modern GenAI architectures including retrieval-augmented generation (RAG), tool-using agents, evaluation frameworks, and guardrails.
• Comfortable designing cloud-native architectures across AWS, GCP, or Azure, with working knowledge of containers, networking fundamentals, and security best practices.
• Able to whiteboard distributed training or inference architectures and then implement working prototypes that demonstrate real customer value.
• Excellent communication and storytelling skills, with the ability to translate complex technical concepts into business impact.
• Thrives in fast-paced environments and can manage multiple customer engagements simultaneously.

Preferred:

• Experience building and evaluating agentic applications using frameworks such as LangChain, DSPy, LlamaIndex, CrewAI, OpenClaw, or similar ecosystems. Ability to quickly adapt to new frameworks is a huge plus.
• Familiarity with vector databases, embeddings workflows, and LLM evaluation frameworks (e.g., Ragas, TruLens, DeepEval).
• Hands-on experience with Hugging Face Transformers, PEFT/LoRA/QLoRA fine-tuning, TRL, Unsloth, or similar fine-tuning stacks. Big plus if experience using RL to improve agentic systems. 
• Experience operating distributed workloads using Slurm, Ray, or Kubernetes.
• Experience with inference optimization and serving frameworks such as vLLM, TensorRT-LLM, Triton, or TGI.
• Experience in MLOps/LLMOps platform engineering or supporting enterprise AI deployments.

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. 

Lyft Ads is one of Lyft’s newest and fastest-growing businesses, focused on building the world’s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey—before, during, and after a ride—by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes.

We are seeking an Algorithms Scientist  to help build the next generation of ads relevance, targeting, optimization, and measurement algorithms that power the Lyft Ads platform. In this role, you will work across large-scale datasets and complex real-time systems to design, prototype, and deploy production-grade machine learning models. You’ll collaborate closely with Engineering, Product, Data Science, and Sales to translate ambiguous business and advertiser needs into rigorous algorithmic solutions that improve ad performance, enhance marketplace efficiency, and drive meaningful revenue growth.

This is a high-impact, highly technical role within a rapidly scaling business line. The ideal candidate brings strong applied machine learning intuition, hands-on modeling experience, and the ability to write clean, efficient production code. You will play a critical role in shaping how advertisers connect with Lyft riders—pushing the boundaries of personalization, measurement, and real-time optimization in a dynamic marketplace.

Responsibilities:

• Design, develop, and deploy production-grade machine learning models and algorithms that power core Lyft Ads capabilities, such as ad relevance, targeting, ranking, bid optimization, pacing, campaign delivery, and measurement.
• Own the end-to-end lifecycle of modeling projects — including problem definition, data exploration, feature engineering, model development, offline evaluation, deployment, and monitoring.
• Collaborate closely with Ads Engineering to integrate models into real-time ad-serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.
• Analyze large-scale mobility, behavioral, and ads performance datasets to identify patterns, surface opportunities, and guide ML and AI driven product improvements.
• Implement rigorous model evaluation frameworks, including offline metrics, statistical tests, calibration, sensitivity analysis, and A/B experimentation to validate both model impact and system-level outcomes.
• Build robust training pipelines, feature transformations, and scoring infrastructure, ensuring reproducibility, observability, and long-term maintainability.
• Partner with Product, Engineering, and Sales to translate ambiguous advertiser goals (e.g., increased conversions, reach efficiency, brand lift) into measurable requirements and success metrics.
• Investigate and resolve model behavior issues, production regressions, calibration drift, and performance anomalies in close partnership with Ads Infra teams.
• Drive innovation by staying current with advances in ML for ranking, recommendation, causal inference, optimization, and ads measurement — and proactively identifying opportunities to apply them.
• Contribute to Lyft Ads’ modeling and experimentation infrastructure, through model cards, documentation, reproducibility standards, and code quality improvements.

Experience:

• Master’s, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience.
• 3–5 years of hands-on ML/applied science experience, ideally involving production models, large-scale systems, or ads/recommendation/relevance domains.
  Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn; ability to write clean, efficient, production-adjacent code.
• Experience working with large-scale datasets and distributed data tools (Spark, Snowflake, Presto, Databricks).
• Practical experience building and evaluating:
• Ranking and relevance models
• Optimization or pacing algorithms
• Predictive models for CTR, CVR, or user response
• Causal or experimentation-based measurement methods
• Understanding of online/offline evaluation techniques, including:
• Offline metrics (AUC, NDCG, MRR, calibration)
• A/B testing methodologies
• Bias correction and counterfactual estimation
• Ability to solve ambiguous problems by structuring analyses, evaluating trade-offs, and proposing algorithmic solutions grounded in scientific rigor.
• Strong communication skills, with an ability to clearly explain model behavior, constraints, trade-offs, and recommendations to engineering, product, and sales partners.
• Demonstrated ownership of modeling work, including debugging, monitoring, documentation, and iteration after deployment.
• Curiosity, initiative, and a track record of delivering measurable improvements through high-quality modeling.

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $128,000 - $160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Total compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process. 

About The Role 

As a Technical Account Manager, you will become the bridge between Hightouch and our largest Fortune 5000 customers. You will oversee the entire customer journey starting from kick-off to onboarding to continued customer success and finally, increased adoption. You are a product expert and will leverage your knowledge to ensure our Enterprise customers understand and utilize the Hightouch platform to its fullest extent and beyond.

In this role, you strive to understand customer requirements and issues at the molecular level. No matter your background, you have a natural curiosity to uncover a customer’s use case and help navigate to the most elegant and efficient solution. Fundamentally, you are enamored with how a company can utilize data to its fullest extent. Utilizing this curiosity and knowledge, your goal is to guide the customer into their ideal future state as well as guide the innovation of the Hightouch platform as well.

What You’ll Do

• As a critical member of the Customer Success team you will be responsible for the retention and expansion our largest Enterprise customers
• You will be part of a team that will work closely with Sales to strategize on how to increase the adoption of Hightouch within large organizations
• From a technical perspective, your primary responsibilities will be to deliver a timely and organized onboarding for customers through effective project management, ensure customers see the full value in Hightouch’s products, and advise on technical best practices
• Provide customers with clear proactive technical guidance and expertise across all our products
• Collaborate with Customer Support, Engineering, and other teams to assist with technical escalations
• Contribute towards the success of the Hightouch platform by surfacing use cases and problems to Engineering that push our product to the next level

What We're Looking For

• 5-10 years of experience in a client facing and / or technology focused role where business experience and technical acumen was combined
• Experience managing and executing technical projects with a customer-first attitude and a strong sense of empathy
• Excellent project management and communication skills
• Proven ability to quickly learn new technologies and understand complex systems (SQL, databases, APIs, reporting tools, etc.)
• Strong troubleshooting and problem solving skills with a continuous desire to improve your technical acumen
• Ability to collaborate cross functionally with different teams and types of people
• Ability to work under pressure, deadlines and navigate unexpected roadblocks with ease

We are looking for a Staff Security Software Engineer who is passionate about detecting and mitigating abuse in the Cloud. 

As a Staff Security Software Engineer at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. This role reports to the Senior Manager of Security Engineering within the Security organization. You should have experience developing and maintaining software systems in a complex, high-scale environment, analyzing outcomes and communicating insights to stakeholders, and rapidly devising solutions that are in alignment with overall business goals. Our team is focused on enabling DigitalOcean to scale safely by building systems that detect and prevent abuse on our platform. We highly value collaboration and growth, and work closely with other teams in the Security organization to deliver high quality solutions and also build tooling to boost their efficiency.

Our customers trust us with their data and operations, and we take that responsibility seriously. Security at DO means solving highly complex problems on a large scale that have real impact for our customers, our products, and for the larger internet community.

What You’ll Do:

• Design, develop, and deploy resilient services and tooling that provide security capabilities at scale, primarily in Go, with some work in Javascript and Python.
• Research and design automated approaches to detecting and actioning abuse and misuse of DigitalOcean products and services.
• Work with product and engineering teams to design and implement secure architectures.
• Design and build internal tools that enable our Security Operations Center to do more, faster.
• Measure the efficacy of our services and tools, using logs, metrics, and audit records, to drive reporting and decision-making, leading to iterative and transformative security improvements as DigitalOcean scales. All while being mindful that security should be an efficiency enabler for the business, not an obstacle.

What You’ll Add to DigitalOcean:

• 8+ years of hands-on experience in software engineering projects, ideally with a security focus, in a complex, high-scale SaaS or IaaS environment. You are an expert in writing robust code with good test coverage and demonstrated success in delivering projects.
• Understanding of cloud-native services and infrastructure provisioning (e.g. compute, storage, networking).
• Deep familiarity with cloud services & infrastructure—compute, storage, network, managed services—and related abuse tactics, including DDoS, spamming, phishing, cryptomining, and bot networks.
• Strong analytical and reporting skills, with proficiency in SQL and data warehouse querying (e.g., Snowflake, Redshift, BigQuery)
• A customer-first mindset—you aim to maximize abuse prevention while avoiding false-positives that could impact high-value customers.
• Excellent communication and documentation skills; you can clearly articulate patterns, mitigation strategies, and tradeoffs to both technical and non-technical stakeholders. You have a record of partnering with internal engineering teams and non-technical stakeholders to gather requirements and tackle security problems across an entire stack with empathy and creativity.
• High integrity, strong judgment, and a track record of working independently on high-impact investigations and policy decisions.

Bonus qualifications:

• Experience with microservice architectures, asynchronous and event-driven processing, and synchronous gRPC/HTTP-based requests.
• Experience in building secure by default services and applications.
• Familiarity with technologies such as gRPC, Docker, Elasticsearch, Prometheus/VictoriaMetrics, Kubernetes, and GitHub Actions.
• Experience with Looker, Snowflake, dbt, and Airflow

Compensation Range: 

• $199,680 - $249,600

*This is a remote role

#LI-Remote

Senior Manager, Data Science

Portfolio Management and Loss Mitigation

The Role: 

SoFi is seeking an inspirational and deeply experienced Senior Manager to lead the Portfolio Management and Loss Mitigation function in our Risk Data Science team. Reporting to the Head of Risk Data Science, this role will lead the development, deployment, and governance of portfolio management and loss mitigation models for all credit products.

The ideal candidate is a hands-on leader who can transition the team from traditional modeling to next-generation machine learning platforms, leveraging emerging data sources (e.g., cash flow, alternative bureaus) to significantly improve portfolio performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence stakeholders, and proven success in delivering complex models into a regulated production environment.

What You'll Do: 

• Portfolio Management and Loss Mitigation Excellence: Directly oversee the development and deployment of Next Generation models designed to manage and mitigate portfolio losses while maintaining loss guardrails.
• Drive Next-Generation Capabilities: Incorporate industry trends and advanced techniques (NLP, Graph Mining, LLMs, Deep Learning) to solve complex, high-impact risk problems where established principles may not fully apply.
• Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (Macro-Economic variables, tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.
• Lead the current team of high-performing Staff and Senior Data Scientists. Recruit, mentor, and foster talent through deliberate interactions, succession planning, and creating a high-accountability, low-ego culture.
• Model Risk Management (MRM): Act as the primary owner for all models in the portfolio, ensuring robust documentation, monitoring, and successfully navigating the 2nd Line of Defense (2LOD) review and approval process (SR 11-7 familiarity is mandatory).
• Stakeholder Alignment: Interact and negotiate with senior management and external stakeholders to reconcile competing views and drive critical, high-impact business decisions.
• Automation and Efficiency: Lead efforts to automate model monitoring and governance processes to create scalable and auditable infrastructure.

What You'll Need:

• Experience: 8+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 3 years in a people management role, managing technical staff.
• Education: Master’s or Ph.D. degree in a quantitative field (Statistics, Computer Science, Engineering, Operations Research, etc.).
• Technical Acumen: Deep expertise in advanced statistical and machine learning modeling techniques (e.g., Gradient Boosting, Deep Learning, Causal Inference).
• Regulatory Knowledge: Detailed working knowledge of model risk management standards (e.g., SR 11-7) and the ability to operate within a highly regulated environment.
• Tools & Platforms: Expert-level proficiency in Python (PySpark, scikit-learn, TensorFlow/PyTorch) and SQL/data warehouse technologies (e.g., Snowflake, Hive). Familiarity with modern MLOps platforms and cloud computing (AWS).
• 3+ years of progressive people management experience is required, including the ability to recruit, mentor, and foster talent within a team of high-performing Staff and Senior Data Scientists.
• Communication: Ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.

About the role

Are you passionate about using data and AI to shape the future of Faire's Go-to-Market (GTM) strategy, sales, and operations? If so, we want to talk to you! We're looking for a technical owner in our team to work closely with Revenue Operations, GTM Systems Engineers, Data Scientists, Product Analysts and Software Engineers to support revenue-driving GTM initiatives by designing and building scalable data capabilities that inform and drive insights. You will lead the path in using AI to boost productivity and transform how analytical engineering operates—leveraging AI to streamline data pipeline development and operations, improve GTM data consumption workflows (e.g., Snowflake, BI tools, Salesforce), and automate routine analytical tasks. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly. 

Join us and be part of a team that values data-driven innovation and excellence.

What You Will Do

The ideal candidate will possess a perfect blend of data engineering technical expertise and the product sense to be able to translate internal customer needs into practical solutions. They will have strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on GTM data initiatives. 

• Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners.
• Lead the technical execution in building scalable data models and pipelines for a GTM domain defining the architecture, data requirements, and roadmap (e.g., Contact Scoring, Lead Qualification, Sales Pipeline, Sales Enablement).
• Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.
• Redefine how we build, maintain, and scale data systems by embedding AI into our daily workflows.
• Optimize processes for operational excellence in project management and system reliability.
• Ensure security standards are met within data systems and workflows. 
• Ensure and promote data quality standards for accurate and reliable insights.
• Embrace emerging technologies with enthusiasm.

Minimum qualifications

• 4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases.
• Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.
• Production-level development experience in Python.
• Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
• Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.
• Experience with Airflow, Docker, DBT or similar analytics workflow tools.
• BA/BS degree in Computer Science, Math, Physics, or a related technical field. 

Nice-to-haves

• Experience with GTM specific data modeling using a BI tool such as Looker or similar while leveraging conversational analytics. Build and own the GTM semantic layer.
• Hands-on experience with GTM-specific data and platform apps, including Reverse ETL (e.g., Hightouch), ELT/Ingestion tools (e.g., Fivetran), iPaaS/Integration platforms (e.g., Workato, N8N, Zapier), and CRM/GTM systems and tool (e.g., Salesforce, Clay).

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

The Mission

Panther is building the future of SOC automation through AI agents that fundamentally change how security teams operate. Our vision is to enable SOC teams to cover 5-10x more data without proportionally scaling headcount by automating the most time-intensive analyst work: alert triage, analysis, and risk validation. We're building intelligent agents that leverage our data pipeline and alerting capabilities to create a SOC team extension that gets smarter over time through collective intelligence.

The Team + Role

You'll build and lead Panther’s agentic team focused on AI-powered SOC analyst solutions that sit at the intersection of security and cutting-edge ML engineering. This is a customer-centric product engineering leadership role where you'll own the execution of our product roadmap, be the bridge between Engineering and Product Management, and you’ll build and lead the team through change alongside our customers, the industry and within the security domain. We're building autonomous security capabilities for alert triage, interactive chat, detection code generation, and text-to-search, all deeply integrated with Panther's ingestion pipeline. This role is ideal for a leader who combines strong people management skills and B2B product engineering experience within the security domain; SOC automation and XDR.

What You'll Need

• Leadership & People Management:
  • 5+ years of people management experience leading product engineering teams
  • Proven track record of hiring, developing, and retaining high-performing engineers
  • Experience managing cross-disciplinary teams and owning all aspects of people leadership
  • Strong partnership skills with recruiting teams to scale headcount effectively

• Business & Product Acumen:
  • Experience working in product-sales environments with direct customer exposure
  • Experience operating in ambiguous environments and making strategic decisions with incomplete information
  • Track record of owning the partnership between Product, Design and Engineering to define vision and roadmap
  • Experience owning user-facing product features from conception to delivery

• Technical Foundation:
  • Experience scaling a team focused on building agentic products and driving ai lead outcomes.
  • Technical depth to participate in architecture discussions and unblock teams on complex design decisions
  • AWS experience preferred (serverless architectures, cloud infrastructure)
  • Cybersecurity background is a nice-to-have but not required
  • Familiarity with modern engineering stacks (Golang, React, TypeScript, GraphQL) helpful

• Mindset:
  • Customer-obsessed: You understand that your team's integrations are the first experience customers have with Panther
  • Owner mentality: You take responsibility for outcomes, not just outputs
  • Team-focused: You prioritize team health, growth, and sustainability alongside delivery

What You'll Do

• • Lead and grow Panther's AI team — hire, develop, and retain engineers working at the intersection of security and AI, building the capabilities that will define Panther's next chapter as a mature AI SOC platform.
  • Own the AI team's delivery — drive execution of the roadmap across autonomous alert triage, interactive chat, detection code generation, and text-to-search, balancing velocity with technical quality.
  • Build Panther's SOAR capabilities using AI infrastructure — lead the team in developing a next-generation Security Orchestration, Automation, and Response solution that leverages Panther's AI infrastructure, MCP integrations, and AI policy framework to automate analyst workflows at scale.
  • Shape the AI SOC platform strategy — partner with Product and the Director of Engineering to define and evolve the roadmap across critical verticals: agentic triage, MCP-powered integrations, AI policies, and collective intelligence.
  • Drive technical direction without coding — participate actively in architecture discussions, challenge design decisions, unblock the team on complex problems, and raise the bar on how we build agentic systems, LLM pipelines, and security automation.
  • Operate with a security-first mindset — collaborate with the broader engineering org on reliability, on-call health, and security practices, ensuring AI features meet the trust and compliance standards Panther's customers expect.
  • Contribute to engineering-wide leadership — participate in hiring loops, share learnings across teams, and help shape how Panther builds and scales its engineering organization as we grow.

We believe in transparency throughout our process — including how we approach AI.

We recognize that AI tools can enhance productivity and support high-quality work. Candidates are welcome to use AI tools for assistance when preparing application materials and completing take-home assignments. If AI use is not permitted for a specific assessment, we will indicate that clearly in the instructions. During live interviews, we ask that candidates not use AI tools to generate or supply real-time answers. This includes reading from AI-generated responses or prompts during conversational, behavioral, or technical discussions. These conversations are designed to understand your individual thinking process, problem-solving approach, and ability to communicate your ideas.

We also use AI tools to support our recruiting processes; hiring decisions are made by our team, not AI.

Reasonable Accommodations
We are committed to providing equal opportunity to all candidates. If you require the use of an AI-based tool or any other assistive technology as a reasonable accommodation for a disability or medical condition, please notify us prior to your interview. We will engage in an interactive process to determine what arrangements are appropriate for your situation. Accommodation requests are handled individually and in accordance with applicable law.

About Panther

Panther makes security teams smarter and faster than attackers.

We're building the AI SOC platform that modern security teams need. Our Detection-as-Code approach, cloud-native architecture, and powerful security data lake help teams detect and respond to threats at scale. Security teams at leading companies use Panther to protect their organizations without the overhead and costs of legacy SIEM solutions.

Founded by security practitioners who lived the pain of protecting large organizations, we've raised $140M from Coatue, Lightspeed, ICONIQ Growth, Snowflake Ventures, and others. We're a global, remote-first company serving customers worldwide.

Our culture is built on flexibility, transparency, and collaboration. We operate by three core values: Create Customer Love, Be an Owner, and Take Care of the Team. We believe diverse perspectives make us better, and that building great security technology should also mean building a rewarding place to work.

The Perks

• Competitive equity in a well-established cybersecurity company
• Unlimited PTO with a 15-day minimum, plus local federal holidays
• Latest tech equipment and budget for your personalized setup
• Comprehensive health and benefits coverage
• Remote-first culture built for distributed teams

Panther Labs is an Equal Opportunity Employer. The Company prohibits discrimination and harassment on the basis of: race, color, national origin, ancestry, sex (including pregnancy, childbirth, breastfeeding), gender, gender identity, gender expression, sexual orientation, marital status, age, religious creed, physical disability, mental disability, genetic information, military or veteran status, or any other status protected by law. All employment decisions are decided on the basis of qualifications, merit, and business need.

The annual cash compensation target: $180,000-$250,000 depending on experience

Why This Role, Why Now

GTM Data Strategy & Operations stood up from scratch with no predecessor. Today the function runs on three offshore contractors and zero FTEs, managed by a single leader who is simultaneously building the agentic infrastructure, operating it in production, and driving major initiatives (hierarchy redesign, data quality assessment, vendor optimization).

The operating model is deliberately agentic AI–first: a multi-agent pipeline (Cartographer, Sentinel, Resolver, Reporting) handles detection, enrichment, hierarchy mapping, and conflict resolution at scale. This is not a future-state vision, these agents are live and processing enterprise account families in production today.

The problem: one person cannot build, operate, and extend this system while also managing strategic workstreams. The function currently covers only core Tier‑1 fields. Dozens of account, contact, and lead signals remain unaddressed. Every pipeline run, every failure diagnosis, and every offshore handoff flows through a single point of failure.

This role is the first onshore execution hire for an agent operator who can keep the system running, improve it, and extend detection and resolution coverage as GTM leadership prioritizes new data elements.

Role Summary

Sit between AI systems and GTM data. Operate, tune, and extend our agentic data quality pipeline (detection, enrichment, hierarchy mapping, conflict resolution) so it runs reliably, improves continuously, and expands to cover more of the data landscape. Own the handoff between automated output and human review, managing quality and throughput with our offshore team. You don’t build agents from scratch, but you run them, evaluate their output with GTM data judgment, and make them better.

Core Responsibilities

Agent Pipeline Operations

• Run and monitor production pipeline sessions (Cartographer, Sentinel, Resolver) across scheduled cadences; diagnose and resolve failures (API errors, session timeouts, data anomalies) without escalating to the function lead.
• Execute pipeline runs in Claude Claude and tmux; manage long-running batch processes; interpret logs and output to confirm data integrity before downstream handoff.
• Maintain pipeline orchestration scripts and configuration; extend agent coverage as new data elements are prioritized by GTM leadership.

Agent Tuning & Improvement

• Refine detection rules, prompt logic, and confidence thresholds based on output analysis and false-positive/negative patterns.
• Evaluate agent accuracy by segment (Enterprise vs. MM/SMB) and recommend rule or workflow changes backed by evidence.
• Run bake-offs (vendor vs. AI enrichment) to optimize cost, coverage, and accuracy; document results for decision-making.

Sentinel → Offshore Resolution Loop

• Own the handoff between Sentinel detection output and Concentrix triage queues; define queue structure, priority tiers, and resolution instructions.
• Monitor offshore resolution quality and throughput; refine detection rules based on patterns surfaced through triage.
• Close the feedback loop: track resolution outcomes back to agent configuration to reduce recurring false positives and improve detection precision.

Data Quality & Enrichment Operations

• Maintain ops-only staging fields; manage the promote-to-production flow with audit controls.
• Design and run AI-assisted enrichment workflows (Clay + LLM prompts) with evidence links and confidence thresholds.
• Monitor fill-rate, sampled accuracy, freshness, and cost-per-record by source and segment; surface vendor performance issues and recommend changes.
• Keep data dictionaries, SOPs, and runbooks current as agents and processes evolve.

Cross-Functional Partnership

• GTM Systems (SFDC): field configuration, permission sets, automation, flows.
• Data Engineering: source availability, ID mapping, lineage (no pipeline coding).
• Reporting: define metrics and acceptance criteria; partner on dashboard requirements.

What to Expect

This is a triage environment, not a steady-state one. The function is young, the data has known gaps, and the work is to stabilize and extend, not maintain and optimize. You’ll be building the plane while flying it, alongside a small team that operates with high autonomy and a bias toward measurable outcomes. If ambiguity and mess energize you, this is the right fit.

Success Metrics (6–12 Months)

Pipeline Reliability

• Scheduled pipeline runs execute without function-lead intervention; failure-to-resolution cycle time under 24 hours for non-blocking issues.
• Agent coverage extended to new data elements as prioritized (measured by number of signals under active detection).

Detection & Resolution Quality

• Sentinel detection precision and recall improve quarter over quarter, tracked by segment.
• Concentrix resolution queue throughput and accuracy meet defined acceptance thresholds.
• False-positive rate decreases through feedback-loop refinement.

Data Quality Outcomes

• Tier-1 field fill-rates: Country ≥95%; Vertical ≥90% at ≥85% sampled accuracy; Revenue bands ≥90%.
• Hierarchy coverage 65–80%+ across target segments.
• Enterprise cost-per-record reduction of 30–40% via AI-first + selective vendor usage.

Qualifications

Required

• 3–6 years in Data Ops, Sales Ops, or GTM Ops with hands-on data quality ownership for account and contact data.
• Proficiency with Snowflake (SQL for querying, analysis, validation) and SFDC (object model, field configuration, data flows).
• Working experience with Claude Code or comparable LLM-based tooling in an operational (not just experimental) context.
• Experience designing and running AI-assisted enrichment workflows (e.g., Clay + LLM prompts) and evaluating accuracy/coverage.
• Comfort operating in a command-line environment: tmux, shell scripts, log analysis, batch process monitoring.
• Process design mindset with a bias toward measurable outcomes; strong written communication.

Strong Plus

• Experience with account/contact data vendors (D&B, ZoomInfo, Clearbit, StoreLeads) and waterfall enrichment logic.
• Python for QA scripting, sampling, or light automation.
• Familiarity with prompt engineering, confidence scoring, and AI guardrails (evidence capture, versioned prompts, QA sampling gates).

Tool Stack

• Core: Snowflake (SQL), SFDC, Claude Code, Clay
• Pipeline: Shell orchestration, Cartographer / Sentinel / Resolver agents
• Enrichment: D&B, ZoomInfo, Clearbit, StoreLeads, LLM prompts
• Nice to Have: Python, SOQL, prompt engineering frameworks
• AI Guardrails (Expected Practice): Confidence floors, evidence capture, versioned prompts, 10% QA sampling gates, audit-on-promote, drift alerts, and privacy/compliance checks. This role is expected to uphold and improve these practices, not just follow them.

Senior Associate, Software Engineer – Data Platform & AI Applications
San Francisco, California 

The Opportunity 

Jordan Park is seeking a Senior Associate to help build and extend our enterprise data platform and AI application ecosystem.

This role combines advanced data engineering, cloud infrastructure, DevOps discipline, and applied AI development. The Senior Associate will operate as a senior individual contributor — owning major platform components while partnering closely with leadership and business teams. This is a hands-on technical role with meaningful scope and influence.

In this role, you will be responsible for enabling trusted analytics across the firm, integrating proprietary data into AI systems, automating operational workflows and creating custom apps and tooling.

Your Role

• Data Platform Engineering
  • Design, build, and maintain production-grade SQL data pipelines (e.g., dbt + Snowflake + Python)
  • Develop and manage orchestration workflows (Airflow or equivalent)
  • Create data ingestion processes and API integrations

• AI Application Development
  • Build and develop the use of AI in the form of: LLM apps, RAG architectures, Custom GPTs & Agent systems
  • Integrate proprietary firm data securely into AI workflows
  • Establish observability standards
  • Translate AI experimentation into production-grade tools

• Cloud Infrastructure (AWS)
  • Support AWS-based infrastructure including VPCs, ECS, EKS, S3, etc.
  • Containerize services using Docker and manage workloads in Kubernetes
  • Establish logging, monitoring standards

• Python Development & Automation
  • Develop Python-based tools for API integrations, data transformations, ad-hoc in-house applications & tooling
  • Build reusable modules and maintain code standards
  • Create automation solutions that reduce manual operational effort

• Projects & Communication
  • Partner cross-functionally with Investment, Client Advisory, Operations, and Finance teams
  • Be self-directed in project management and delivery
  • Translate business requirements into technical architecture
  • Deliver executive-ready summaries of platform and AI initiatives

Qualifications

Required:

• Bachelors degree with 5–8 years of experience in: data engineering, platform engineering, cloud infrastructure
• Requisite experience in AI Application development including LLM APIs and RAG Pipelines
• AWS experience including Docker and Kubernetes
• Advanced Python proficiency
• Advanced SQL and data modeling
• Experience implementing CI/CD and DevOps best practices
• Strong written and executive communication skills
• Experience in wealth management, asset management, or fintech
• A positive, helpful and can-do attitude

Preferred:

• Salesforce data integration experience
• Experience designing secure AI architectures
• Experience mentoring junior engineers

Compensation & Benefits

Compensation at Jordan Park includes a base salary, discretionary year-end bonus, benefits and other perks.  We apply a total reward philosophy when determining compensation terms. The expected base salary for this role in San Francisco, California will range from $125,000 to $160,000 per year commensurate with experience, job-related skills, relevant education, licenses and certifications, and other business and organizational needs. 

Our benefits package includes:  

• Medical, dental & vision insurance – 100% of premium covered for employees
• 401k participation with employer contribution
• Generous paid time off 
• Commuter benefits program (pre-paid tax dollars towards your commute)
• Fitness Reimbursement
• Annual Professional Development Stipend 

Associate, Software Engineer – Data Platform
San Francisco, California

The Opportunity 

Jordan Park is seeking a Technology & Data Engineering Associate to advance our data platform and data quality initiatives. This role operates at the intersection of data engineering, analytics, data quality management, and AI enablement.

The Associate will design, build, and maintain production-grade data systems while partnering directly with executives, investment teams, operations, and client service professionals to drive measurable business outcomes. This is a hands-on technical role with meaningful ownership and visibility.

Your Role

• Data Platform
  • Design, build, and maintain production-grade SQL data pipelines (e.g., dbt + Snowflake + Python)
  • Develop and manage orchestration workflows (Airflow or equivalent)
  • Create data ingestion processes and API integrations
  • Monitor pipeline reliability and performance; proactively resolve issues

• Data Quality & Controls
  • Develop deep expertise in firm data, systems, and processes
  • Design reconciliation frameworks across systems and automate data validation/exception reporting
  • Perform detailed variance analysis and root cause investigations
  • Partner with operations and finance teams to ensure reporting integrity

• Analytics & Business Intelligence
  • Architect and maintain Tableau dashboards used across the firm
  • Train and support internal stakeholders on self-service analytics

• Python Development & Automation
  • Develop Python-based tools for API integrations, data transformations, ad-hoc in-house applications & tooling
  • Build reusable modules and maintain code standards
  • Create automation solutions that reduce manual operational effort

• Projects & Communication
  • Work closely with the Chief Technology Officer (CTO) to deliver clear executive summaries of data findings, operational trends, etc.
  • Document project discovery and project management artifacts
  • Translate technical work into business impact
  • Present findings to senior leadership

Qualifications

Required:

• Bachelors degree with 3–5 years of experience in Data Engineering, Analytics, Business Intelligence or related technical role
• Advanced SQL proficiency (production-level experience)
• Experience with dbt and Snowflake (or similar modern data stack)
• Strong Python skills for data engineering and automation
• Experience with Tableau or similar BI platform
• Strong written and verbal communication skills
• A positive, helpful and can-do attitude

Preferred:

• Experience in wealth management, asset management, fintech, or financial services
• Familiarity with Salesforce reporting and CRM data models
• Experience building AI workflows or internal GPT tools
• Experience with cloud infrastructure (AWS preferred)

Compensation & Benefits

Compensation at Jordan Park includes a base salary, discretionary year-end bonus, benefits and other perks.  We apply a total reward philosophy when determining compensation terms. The expected base salary for this role in San Francisco, California will range from $115,000 to $150,000 per year commensurate with experience, job-related skills, relevant education, licenses and certifications, and other business and organizational needs. 

Our benefits package includes:  

• Medical, dental & vision insurance – 100% of premium covered for employees
• 401k participation with employer contribution
• Generous paid time off 
• Commuter benefits program (pre-paid tax dollars towards your commute)
• Fitness Reimbursement
• Annual Professional Development Stipend 

WHAT YOU’LL DO

As a Technical Support Specialist, you will be a vital member of our Global Customer Support organization—serving as a trusted product expert, primary point of contact for inbound questions and owner of complex technical cases. You’ll diagnose and fix issues, answer product questions, and guide best practices, ensuring fast, accurate help and a great customer experience.

Your responsibilities will include:

• Owning customer inquiries end-to-end (how-to questions, technical break-fix issues, integration/configuration help, and best practice guidance), providing timely, insightful, and technically sound resolutions and suggestions.
• Becoming a trusted product expert—mastering the dashboard, integrations, troubleshooting steps, and best practices
• Driving increased product adoption by enabling customers to effectively utilize the platform and achieve their desired outcomes.
• Collaborating effectively with your own team members, Customer Success, Account Managers, Product and Engineering, and other cross-functional teams to deliver seamless customer experiences.
• Proactively identifying opportunities to enhance customer satisfaction and drive product adoption.
• Contributing to process improvements and internal enablement while actively documenting and sharing knowledge to elevate teammates and customers.

Please note this job description does not cover every duty you may need to undertake; you may be asked by your manager to handle other reasonable responsibilities commensurate with the role.

WHAT YOU HAVE

•  2–3 years of experience supporting technical products, ideally in SaaS or mobile application environments.
• A degree from an accredited college or university, a technical boot camp certification, or equivalent practical experience.
• Proficiency with case management tools (e.g., Salesforce, Zendesk) for efficient inquiry management and resolution.
• Hands-on experience with HTML, CSS, APIs, and/or SQL
• Experience with tools such as Postman, Snowflake, and/or Kibana is a plus.
• Domain knowledge of two or more: SaaS, Mobile Technology, APIs, Marketing Automation, Direct Marketing, Marketing Analytics, and/or basic programming.
• Strong written and verbal communication skills in English

WHO YOU ARE

• An excellent communicator with a customer-centric attitude with the ability to translate complex concepts into clear, understandable language for diverse audiences.
• Analytical, curious, and resourceful with strong troubleshooting and problem-solving capabilities
• Passionate about helping customers and resolving issues efficiently and effectively.
• Skilled at managing and prioritizing a high volume of inquiries and escalations; resilient and calm under pressure in fast-paced, time-sensitive situations.
• Able to synthesize complex technical concepts and communicate them clearly to diverse audiences
• Adaptable to fast-paced, high-volume environments with shifting priorities while being able to multitask and maintain performance under pressure.
• A proactive problem solver with a strong sense of intellectual curiosity, who thrives in collaborative team settings to tackle challenges.

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $78,000 and $90,000/year, with an expected On Target Earnings (OTE) between $80,000 and $105,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

MaintainX is the world's leading Asset and Work Intelligence platform for industrial and frontline environments. We are a modern IoT-enabled cloud-based tool for reliability, safety, and operations on physical equipment and facilities. MaintainX powers operational excellence for 13,000+ businesses including Duracell, Univar Solutions Inc., Titan America, McDonald's, Brenntag, Cintas, Xylem, and Shell.

We recently completed a $150 million Series D funding round, bringing our total funding to $254 million and valuing the company at $2.5 billion.

As the AI GTM Engineer, Growth Marketing, you’ll build and scale the technical foundation behind MaintainX’s acquisition engine. Reporting to the VP, Growth Marketing & Strategy, this is a hands-on, embedded role within the Growth Marketing team, where you will partner directly with marketers to design, build, and launch campaigns powered by automation and AI. You won’t operate as a separate engineering function, you’ll work side-by-side with Customer Marketing, Performance Marketing, SEO & GEO, Lifecycle, and Field Marketing teams to turn campaign ideas into scalable systems and live experiments. This role is critical to building an AI-native, system-driven marketing engine at MaintainX, enabling us to scale acquisition through automation, personalization, and experimentation.

What you'll do:

• Partner with Marketing to Build & Launch Campaigns
• Work directly with Growth marketers to ideate, design, and launch acquisition campaigns
• Translate campaign ideas into scalable systems, automations, and experiments
• Rapidly prototype and iterate on new growth plays (landing pages, outbound, paid, lifecycle)
• Build Systems That Power Campaign Execution
• Develop tooling for programmatic landing pages, ad creative generation, and email workflows
• Enable marketers to launch campaigns faster through reusable systems and automation
• Balance speed (quick tests) with scalability (systems that can be reused)
• Embed AI into Marketing Workflows
• Partner with marketers to identify high-leverage use cases for AI in campaigns
• Build and deploy AI-driven systems for:
• Creative generation and testing
• Personalization across channels
• Outbound messaging and sequencing
• Turn one-off experiments into repeatable campaign infrastructure
• Own Experimentation with Marketing
• Co-design and implement experiments across paid, SEO, lifecycle, and web
• Build tooling to track performance, attribution, and testing outcomes
• Enable faster, data-driven iteration across campaigns

Audience, Segmentation & Personalization

• Partner with marketers to define target audiences and ICP segments
• Build systems to dynamically segment, enrich, and activate audiences across channels
• Enable real-time personalization across the funnel

• Marketing Data & Performance
• Ensure clean data flows from marketing channels into CRM and analytics systems
• Build dashboards and reporting layers for campaign performance and funnel metrics
• Improve visibility into CAC, conversion rates, and pipeline generation 

What you’ll bring:

Technical Skills

• Strong programming ability (Python, JavaScript, or similar)
• Experience working with APIs, automation frameworks, and event-driven systems
• Strong SQL skills and experience with data warehouses (Snowflake, BigQuery, etc.)
• Experience integrating tools like Salesforce, HubSpot, Segment, Webflow, etc.
• Experience deploying AI/LLM workflows into production
• Marketing Systems Experience
• Experience working closely with marketing teams to build and launch campaigns
• Strong understanding of paid media, SEO, lifecycle marketing, and web conversion flows
• Experience building systems that directly support campaign execution and optimization
• Mindset
• Thinks like a marketer, builds like an engineer
• Optimizes for speed, iteration, and measurable impact
• Focused on pipeline and revenue outcomes, not just outputs
• Defaults to automation and scalable systems over manual work

About you:

• 5+ years in growth engineering, marketing engineering, or technical growth roles, with experience building systems that support marketing and acquisition.
• Strong ability to partner with marketers to design and launch campaigns, and translate those into scalable systems and automation.
• Proficiency in SQL and at least one programming language (e.g., Python, JavaScript), with experience building scripts, workflows, or internal tools.
• Experience working with APIs, data pipelines, and integrating marketing tools (e.g., Salesforce, HubSpot, Segment).
• Experience applying AI/LLMs to automate or scale marketing workflows (e.g., content generation, personalization, outbound).
• Solid understanding of paid media, SEO, lifecycle marketing, and experimentation frameworks.
• Strong analytical skills with experience in testing, attribution, and performance measurement.
• Entrepreneurial mindset: thrives in fast-paced, test-and-learn environments with a bias toward speed and execution.
  
  

What’s in it for you:

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrolment program.
• Take what you need PTO.
• A Work Culture where:
• You’ll work alongside folks across the globe that reflect the MaintainX values, Smart Humble Optimist.
• We believe in meritocracy, where ideas and effort are publicly celebrated.

About us:

Our mission is to make the life of blue-collar workers easier worldwide by creating software that meets their needs and realities. Our product is truly life-changing for 80% of the workforce that doesn’t work behind a desk and needs enterprise-grade software at their fingertips.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.