ABOUT THE TEAM

The People Analytics team is at the forefront of transforming how we understand and optimize our workforce. We are a dynamic group of analytical thinkers and storytellers who leverage advanced analytics and robust methodologies to create strategic insights from complex HR data. Collaborating closely with HR Business Partners, Program Management Teams, Business Operations, Talent Acquisition and various cross functional stakeholders we provide actionable insights that drive informed decisions across the entire employee lifecycle; from optimizing talent acquisition and development to enhancing engagement and retention. Our work directly shapes a thriving employee experience, fuels organizational growth, and ensures our people strategy is truly data-driven.

ABOUT THE JOB

This role is central to our People Data & Analytics team, where you will be instrumental in building and maintaining the robust data infrastructure that powers our strategic insights. You'll own the full data lifecycle, from ensuring accurate ingestion and integration of diverse HR data sources, to designing, developing, and optimizing data models and pipelines. Your primary objective will be to transform raw, disparate information into clean, reliable, and analytics-ready datasets, empowering our People Analysts and business stakeholders to unlock deeper understanding of our workforce, enhance employee experience, and drive data-driven decision-making. Success in this role requires a strong technical foundation, meticulous attention to data quality, and a passion for crafting efficient data solutions.

WHAT YOU'LL DO

• Design, build, and optimize robust ETL/ELT pipelines to reliably ingest, integrate, and transform diverse people data from various HR systems (HRIS, ATS, LMS, etc.) into our data platform.
• Develop, maintain, and govern scalable and secure data models, schemas, and ontologies specifically for people analytics, ensuring data quality, consistency, and accessibility for downstream consumption.
• Contribute to the strategic design, development, and evolution of our people data platform and tooling, advocating for engineering best practices, automation, and a scalable analytics ecosystem (e.g., leveraging SQLMesh, Iceberg, Flyte).
• Partner closely with People Analysts, HR Business Partners, and other stakeholders to understand their analytical needs and translate them into robust data solutions, providing well-structured, documented, and reliable datasets.
• Implement and monitor data quality checks, identify discrepancies, troubleshoot data issues, and ensure the reliability and integrity of people data across all systems.
• Continuously monitor the performance of data pipelines and models, identifying bottlenecks and implementing solutions to ensure the efficiency and scalability of our people data infrastructure.
• Create and maintain comprehensive documentation for data pipelines, models, and processes, and champion data engineering best practices (e.g., version control, testing, CI/CD) within the team.
• Implement and enforce strict data security measures and ensure all data handling practices comply with internal policies and external regulations (e.g., GDPR, CCPA) related to employee data privacy.
• Collaborate with broader enterprise analytics and data engineering teams to align on data architecture standards, integrate people data with other business domains, and contribute to the overall evolution of the company's data platform.

REQUIRED QUALIFICATIONS

• 5-7 years of progressive experience in Data Engineering, Analytics Engineering, or a similar role focused on building and optimizing data pipelines and data infrastructure.
• Expert-level proficiency in SQL for complex data manipulation and querying, and advanced Python for scripting, data processing, and automation.
• Extensive experience with cloud-based data warehousing solutions (e.g., Snowflake, Google BigQuery, AWS Redshift, Databricks/Delta Lake) and data lake technologies (e.g., AWS S3, Azure Data Lake Storage).
• Deep understanding and proven experience in designing, implementing, and maintaining robust data models (e.g., dimensional modeling, Kimball methodology) for analytical purposes.
• Hands-on experience building and optimizing complex ETL/ELT processes and data pipelines using modern tools such as dbt, Apache Airflow, Flyte, Dagster, or similar orchestration platforms.
• Excellent communication skills, both written and verbal, with the ability to translate technical concepts for non-technical stakeholders and collaborate effectively across diverse teams.
• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
• Strong technical foundation in data engineering, with expertise in SQL, Python, and experience working with cloud-based data platforms (e.g., AWS, GCP, Azure).

Preferred Qualifications:

• Experience with big data processing frameworks (e.g., Apache Spark, Flink) and advanced data warehousing features like schema evolution or time travel (e.g., Apache Iceberg, Delta Lake).
• Direct hands-on experience with tools mentioned in our stack like Palantir Foundry, SQLMesh, Flyte, or similar cutting-edge data orchestration and transformation platforms.
• Relevant professional certifications from major cloud providers (e.g., AWS Certified Data Analytics - Specialty, Google Cloud Professional Data Engineer).
• Experience with tools like Terraform, CloudFormation, Docker, or Kubernetes for managing data infrastructure and deploying applications.
• Familiarity with integrating data pipelines with leading BI tools (e.g., Tableau, Power BI, Looker) to optimize dashboard performance and data accessibility for end-users.
• Deep expertise working with data from specific enterprise HRIS systems like Rippling, Workday, and Oracle HCM Cloud including their data models and APIs.
• Solid understanding of HR data concepts, metrics, and common HR systems (HRIS, ATS, LMS), with a strong interest in People Analytics.

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: 

• $166,400 - $208,000

*This is a remote role

#LI-Remote

Data is at the heart of every decision at Klaviyo. Our Analytics Engineering team sits within a hub-and-spoke model, partnering closely with Go-To-Market (GTM), Product, Engineering, and Business Intelligence teams to build scalable, trusted data systems. You’ll work at the intersection of business and engineering, owning core data models, enabling self-service analytics, and ensuring our data ecosystem is reliable, scalable, and compliant.

About the Role

We’re looking for a Senior Analytics Engineer to own end-to-end data pipelines and modeling across GTM (Sales) and Product domains. You’ll build and maintain the source of truth for operational and product data, enabling leadership, analysts, and product teams to answer complex questions with confidence. This role combines deep technical execution with high-impact business partnership, requiring you to translate ambiguous needs into scalable data products. You will operate as a trusted, embedded partner to stakeholders while leveraging the broader Data Engineering organization’s standards, tooling, and best practices. You’ll help build the foundation that powers everything from forecasting and compensation to product insights and experimentation. Please note that this is a hybrid role that requires 3 days/week in our Boston office. Fully remote candidates will not be considered at this time. 

How You’ll Make a Difference

• Own and deliver end-to-end data pipelines and models that power Sales and Product analytics
• Build curated, governed data marts that enable fast, reliable decision-making
• Design dimensional data models (dbt) for core entities such as accounts, pipeline, performance, and product usage
• Partner with Sales, Product, and Analytics teams to create holistic views of the customer and product lifecycle
• Raise the bar on data quality, testing, monitoring, and documentation
• Enable reverse ETL workflows to operationalize insights into business systems
• Act as a data ambassador across Product, Engineering, BI, and Legal, ensuring alignment on data contracts and governance
• Lead and mentor others through design reviews, best practices, and technical guidance
• Evolve internal tooling and infrastructure to improve developer and analyst productivity

What You’ll Do

• Data Modeling & Pipelines: Build and maintain production-grade dbt models in Snowflake
• Integrations & Ingestion: Own ingestion from systems like Salesforce, ERP, and product data sources
• Reverse ETL: Push high-value data models into downstream tools and workflows
• Data Quality & Governance: Implement testing frameworks, monitoring, and documentation to ensure trust and compliance
• Cross-Functional Partnership: Work closely with Sales Ops, Product Managers, Engineering, Finance, and GTM teams
• Repository Stewardship: Maintain dbt codebase, enforce best practices, and ensure scalability
• Tooling & Infrastructure: Contribute to Airflow, Terraform, AWS, and other platform tools as needed

Who You Are

• 5+ years of experience in analytics or data engineering in a modern data stack (Snowflake, BigQuery, or Redshift)
• Strong expertise in SQL and dbt, with a focus on building scalable, production-grade data models
• Proficiency in Python (or similar) for orchestration or tooling
• Experience owning end-to-end data workflows, from ingestion to business impact
• Ability to translate ambiguous business needs into structured data solutions
• Strong communication skills with the ability to partner with non-technical stakeholders
• Experience implementing data testing, monitoring, and governance frameworks
• Proven ability to lead cross-functional projects with minimal guidance

Nice to Have

• Experience with Sales Operations, compensation, or GTM analytics
• Familiarity with reverse ETL tools and workflows
• Experience with Airflow, Fivetran, Workato, or similar tools
• AWS experience (S3, EC2, Lambda) and infrastructure-as-code (Terraform)
• Exposure to experimentation frameworks or product analytics systems
• Experience with data privacy controls (masking, role-based access, compliance)

At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit careers.klaviyo.com to see how we empower creators to own their own destiny.

We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 3, 2025.

Please see the independent bias audit report covering our use of Covey here

Are you passionate about data? How about leveraging data to drive meaningful impact across a fast growing two-sided marketplace? Have opinions on how to best enable data scientists across a billion-dollar company to do elastic workforce planning or real-time customer lifetime value prediction? Then we should definitely talk!

The Data Technology team at ezCater is growing! As we look towards the second half of 2025 and beyond, data is a key strategic component across the company - from advanced, real-time machine learning to business intelligence and data governance. Data is our differentiator and how we will drive real, meaningful impact to the $100+billion Catering industry.

We are hiring a Senior Data Engineer to join our expanding team in solving complex data and platform challenges to accelerate our growing business. The ideal candidate lives and breathes data while driving systems and architecture best practices. They care about driving business impact through producing solid and efficient infrastructure alongside accurate and performant data.  You will have the opportunity to work directly with executive stakeholders as we embark on a massive-scale data modeling effort across the organization, so flexibility and the ability to translate business requests to implementation are key.

What you’ll do:

• Write and ship a lot of code.
• Work directly with analysts and stakeholders to refine requirements, nail down logic, and debug and qualify produced data sets to ensure they meet the underlying business needs.
• Drive architectural decisions and thoughtfully balance trade-offs in system design.
• Lead cross-functional data initiatives.
• Champion high standards in data quality, security, and discoverability.
• Translate complex technical challenges into clear solutions.
• Design and develop high-performance data pipelines. Adhering to SDLC, including CI/CD and best practices.
• Identify and drive opportunities to optimize and/or scale existing parts of our stack.
• Utilize tooling and automation to improve developer efficiency.
• Monitor data systems to ensure quality and availability while seeking to drive down costs.
• Contribute to the team processes and community.
• Mentor other Data Engineers.
• Be part of our innovation and transformation story.
  
  
  

What you have:

• Strong experience with data warehousing, data lakes, ELT process, and enterprise data platforms such as Snowflake (preferred), Redshift & BigQuery.
• Experience with building performant data pipelines across disparate systems.
• Experience with cloud platforms such as AWS (preferred), GCP & Azure.
• Mastery in SQL and experience in Python.
• Ability to work independently and collaboratively.
• Willingness and ability to be part of an on-call rotation, occasionally working non-business hours to address critical system alerts and maintain service uptime.
• An open mind and willingness to be flexible. We have a large and complex business, and believe in driving real value out of every project we do.
• Our stack is Snowflake, dbt, Fivetran, Airflow, AWS, Sagemaker, MLFlow, Kubernetes + Docker, Monte Carlo, Hightouch and Python for custom ETL and data science integrations. Experience with the above is a nice-to-have, and a desire to learn is a must.
• Experience with marketing data is preferred, but not required. 
• Ability to travel up to 5 days per quarter for Together Weeks, team gatherings and other events, when applicable.
• A sharp mind, a soft heart and a large funny bone.
  

The national total target cash compensation range for this position, including base salary and bonus target, is $158,000–$190,000 annually.*

*Please note: Final offer amounts are determined by multiple factors, including prior experience, expertise and region & may vary from the amount above. This range does not represent additional compensation benefits (such as equity, 401K or medical, dental or vision insurance).

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

About Toast

At Toast, we're building the restaurant platform that helps restaurants adapt, take control, and thrive. The Customer Success (CS) organization plays a pivotal role in helping customers get the most out of our products and we're transforming our data capabilities to drive a new era of proactive, data-informed customer engagement. 

The CS Data & Analytics team is at the center of this transformation, building the data infrastructure that makes proactive, data-informed customer engagement possible at scale for ~150,000 restaurant locations.

Role Overview

You'll be a founding member of a newly chartered data engineering function within Customer Success, with a direct hand in shaping the architecture, tooling, domain model, and team culture from day one. This is a rare opportunity to build something from greenfield, with visibility to VP and senior CS leadership.

As an Analytics Engineer on the Customer Success Data & Analytics team, you'll bridge the gap between raw data and business-ready insights. You'll build the semantic layer, dbt models, and analytics datasets that power reporting, dashboards, and AI-driven workflows across the CS organization. Reporting to the Director of Data Infrastructure & Engineering, you'll work closely with Data Engineers, Analysts, and CS operations leaders to ensure data is not just available but trusted, consistent, and decision-ready.

This is a hands-on role focused on data modeling, metrics standardization, and analytics infrastructure, with a direct line to CS outcomes like customer retention, agent performance, and proactive customer engagement.

A day in the life (Responsibilities) 

• Build and maintain dbt models that transform raw CS source data from systems like Salesforce, Five9, Intercom, NICE, and LevelAI into clean, analytics-ready datasets across CS domains including Customer 360, case management, omnichannel interactions, and agent performance.
• Design and own the semantic and metrics layer for CS KPIs including customer health scores, CSAT, case resolution rates, handle time, and retention signals, ensuring consistent definitions across all reporting surfaces.
• Partner with CS analysts and business stakeholders to translate reporting requirements into reusable, well-documented data models.
• Implement data testing, validation, and observability frameworks to ensure CS data assets are reliable and trustworthy at all times.
• Contribute to self-service analytics enablement by building datasets and semantic models in Snowflake and Sigma/Hex that allow CS analysts and operations leaders to answer questions independently.
• Collaborate with Data Engineers to ensure upstream pipeline outputs are modeled correctly and fit for purpose for analytics use cases.
• Establish and enforce data modeling standards, naming conventions, and documentation practices that scale as the team grows.
• Support AI and ML use cases by building clean, structured feature datasets for customer health scoring, churn prediction, and agent assist models.
• Participate in code reviews, design discussions, and technical architecture planning to continually raise engineering standards.
• Ensure data pipelines, storage, and access patterns adhere to BTT data standards, security policies, and compliance requirements.
• Partner with BTT governance forums to align on design patterns, data architecture decisions, and SLA expectations.
• Maintain documentation and metadata for all data assets in accordance with established governance processes.

What you'll need to thrive (Requirements)

• 5 or more years of experience in analytics engineering, data engineering, or a related role with a strong focus on data modeling and analytics infrastructure.
• Expert-level SQL and hands-on experience with dbt for building and maintaining data models in a cloud data warehouse environment.
• Experience with Snowflake or a comparable modern data warehouse such as BigQuery or Redshift.
• Familiarity with BI and analytics tools such as Sigma, Hex, Tableau, or Looker.
• Strong understanding of dimensional modeling, metrics layers, and analytics-ready dataset design.
• Ability to translate ambiguous business requirements from non-technical CS stakeholders into clean, scalable data models.
• Demonstrated ability to implement data quality testing, monitoring, and documentation as a standard practice.
• Demonstrated ability to communicate technical tradeoffs and data concepts clearly to non-technical stakeholders, including operations and business leaders.
• Collaborative working style with experience partnering across Data Engineering, Analytics, and business operations teams.
• Strong problem-solving skills, attention to detail, and a drive to build scalable, reliable systems.
  
  

What will help you stand out (Non-essential Skills/Nice to Haves)

• Experience building and optimizing data systems that operate at significant scale, managing billions of records across multiple data domains and systems, with the foresight to design for 5-year growth and future platform scale.
• Comfort using AI-assisted development tools such as GitHub Copilot, Claude, or Snowflake Cortex AI to accelerate pipeline development, testing, and documentation, and curiosity about how GenAI can enhance data product quality.
• Experience with real-time data streaming using Kafka, Kinesis, or Pub/Sub.
• Exposure to data governance, metadata management, and observability tools.
• Background in SaaS or Customer Success analytics, including usage data, retention metrics, and customer health.
• Experience working with CS or CX-adjacent source systems such as Salesforce, Five9, Intercom, or similar CCaaS/CRM platforms, and familiarity with the data models and integration patterns they produce.
• Knowledge of data security, privacy, and compliance in cloud environments.
• Experience with CI/CD, infrastructure as code, or containerization such as Docker or Terraform.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy

We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

About Toast

At Toast, we're building the restaurant platform that helps restaurants adapt, take control, and thrive. The Customer Success (CS) organization plays a pivotal role in helping customers get the most out of our products and we're transforming our data capabilities to drive a new era of proactive, data-informed customer engagement. 

The CS Data & Analytics team is at the center of this transformation, building the data infrastructure that makes proactive, data-informed customer engagement possible at scale for ~150,000 restaurant locations.

Role Overview

You'll be a founding member of a newly chartered data engineering function within Customer Success with a direct hand in shaping the architecture, tooling, domain model, and team culture from day one. This is a rare opportunity to build something from greenfield, with visibility to VP and senior CS leadership.

As a Data Engineer on the Customer Success Data & Analytics team, you’ll design, build, and scale the data platforms and pipelines that power insights across our Customer Success organization. Reporting to the Director of Data Infrastructure & Engineering, you’ll work closely with Data Infrastructure, Analytics, Engineering, and Product teams to ensure high-quality, reliable data is accessible and actionable.

This is a hands-on engineering role focused on delivering production-grade, scalable, and reliable data systems that support analytics, reporting, and operational decision-making across Customer Success.

A day in the life (Responsibilities) 

• Design, build, and maintain scalable, production-ready data pipelines (batch and real-time) for Customer Success using modern data technologies.
• Develop and evolve data models and schemas that enable reporting, analytics, and machine learning across Customer Success functions.
• Partner with CS operations leaders across care, workforce, and CX to translate business requirements into pipeline and infrastructure priorities, ensuring data work is directly connected to customer retention and operational outcomes.
• Ensure data quality, observability, lineage, and governance are built into every data workflow.
• Implement best practices for cost-efficient, performant cloud-based data infrastructure.
• Contribute to data platform tooling and frameworks that support self-service analytics and reusability across teams.
• Actively monitor and optimize data workflows for reliability, scale, and maintainability.
• Collaborate with cross-functional stakeholders to define and track key metrics and ensure consistent data definitions.
• Participate in code reviews, design discussions, and technical architecture planning to continually raise engineering standards.
• Build and maintain semantic and metrics layer foundations (e.g., dbt metrics, Snowflake semantic layer) that enable consistent, reusable definitions of CS KPIs across reporting and analytics surfaces.
• Contribute to the design and evolution of the CS data domain model including Customer 360, omnichannel interaction data, case management, and agent performance in close partnership with cross-functional stakeholders.
  
  

Governance & Standards

Partner with Toast's Business, Technology & Transformation (BTT) organization to establish data governance practices, security policies, and architecture standards that will serve as the foundation for CS data infrastructure. As a founding team member, you'll help define the norms, not just follow them.

• Ensure data pipelines, storage, and access patterns adhere to BTT data standards, security policies, and compliance requirements.
• Partner with BTT governance forums to align on design patterns, data architecture decisions, and SLA expectations.
• Maintain documentation and metadata for all data assets in accordance with established governance processes.
  
  

What you'll need to thrive (Requirements)

• 5+ years of experience in data engineering, software engineering, or a related role building and maintaining data systems in production.
• Strong SQL skills and experience with a programming language such as Python, Scala, or Java.
• Hands-on experience with cloud-based data platforms (AWS, GCP, or Azure).
• Experience building and optimizing ETL/ELT workflows using tools such as Airflow, dbt, or similar orchestration frameworks.
• Deep understanding of data modeling, data warehousing, and pipeline design.
• Ability to write clean, maintainable, and well-tested code for data transformations and automation.
• Demonstrated ability to communicate technical tradeoffs and data concepts clearly to non-technical stakeholders, including operations and business leaders.
• Proven ability to work collaboratively with analytics, operations, and engineering teams.
• Strong problem-solving skills, attention to detail, and a drive to build scalable, reliable systems.
  
  

What will help you stand out (Non-essential Skills/Nice to Haves)

• Experience building and optimizing data systems that operate at significant scale, managing billions of records across multiple data domains and systems, with the foresight to design for 5-year growth and future platform scale.
• Comfort using AI-assisted development tools (e.g., GitHub Copilot, Claude, Snowflake Cortex AI) to accelerate pipeline development, testing, and documentation and curiosity about how GenAI can enhance data product quality.
• Experience with real-time data streaming (Kafka, Kinesis, or Pub/Sub).
• Familiarity with modern data warehouse/lakehouse technologies (e.g., Snowflake, BigQuery, Redshift, Delta Lake).
• Experience with CI/CD, infrastructure as code, or containerization (e.g., Docker, Terraform).
• Exposure to data governance, metadata management, and observability tools.
• Background in SaaS or Customer Success analytics (usage data, retention metrics, customer health).
• Experience working with CS or CX-adjacent source systems such as Salesforce, Five9, Intercom, or similar CCaaS/CRM platforms and familiarity with the data models and integration patterns they produce.
• Knowledge of data security, privacy, and compliance in cloud environments.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy

We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

Location: Remote (US or Canada)
Type: US Applicants - Full-Time; Canadian Applicants - Independent Contractor

About Us

We’re scaling rapidly and have a growing pipeline of opportunities that demand exceptional talent across disciplines. Our mission is to bring on individuals, from creative producers to technical experts to entrepreneurial leaders, who can help us realize this next chapter of growth.

We are a company of doers. Leaders roll up their sleeves, teams work flat, and everyone contributes to what ships. Titles don’t insulate us from feedback or basics. We invite critique, learn quickly, and keep raising the bar. The best ideas win here, no matter where they come from, because clients trust us to deliver the strongest outcomes every time.

Our clients’ missions, products, and bottom lines are sacred. We immerse ourselves in their world, becoming stewards of their goals and partners in solving big problems. Every product, strategy, or asset we create must be both beautiful and functional; practical, usable, and designed for real-world impact.

Humans are our most valuable resource, and we only grow by hiring people who push us forward. Across strategy, engineering, design, data, and operations, we seek out teammates who raise the bar and make us better. Always hire up, never down.

We partner with organizations of all sizes to explore, design, and implement AI strategies that are secure, scalable, and human-centered. We believe AI should amplify human potential, not replace it and we build with that conviction in every engagement. From advisory and tooling to implementation and education, we meet clients where they are at and help them integrate AI in ways that align with their mission and values. Our goal is to empower teams to work smarter, move faster, and unlock new possibilities through thoughtful, responsible innovation.

And through it all, we lead with purpose, love, and adventure. We do meaningful work with people we care about, and we make the ride an adventure worth taking. Because at Human Agency, who we are and how we work are one and the same.

About the role

We’re hiring a Product Lead to join our team and embed directly inside one of our client organizations — a leader in design-build. This role is for a hands-on product builder who thrives on embedding with teams, understanding their workflows, and delivering AI-powered software that drives real value. 

This is not a “strategy-only” role. You’ll spend your time with users, engineers, and executives alike — uncovering needs, setting priorities, and getting solutions shipped. You’ll bring modern product practices into a complex, real-world industry, while raising the bar for excellence in how software gets built.

What you’ll do

Discovery & Prioritization

• Embed with client teams to observe workflows, run discovery, and translate insights into actionable software requirements.
  
  
• Develop and apply structured prioritization methods (balancing user value, business outcomes, and technical feasibility) to guide trade-offs.
  
  
• Keep teams focused on the highest-leverage opportunities, not just the loudest requests.
  
  

Delivery & Execution

• Scope projects with realistic estimates and clear milestones that deliver value early and often.
  
  
• Know how to ship a prototype, gain feedback, iterate to value, and release production-grade solutions.
  
  
• Lead small pods of engineers and operators to ship high-quality, on-time solutions.
  
  
• Facilitate leadership updates and reporting, ensuring execs are aligned and confident in progress.
  
  
• Above all, be able to roll up your sleeves to solve the problem in a way that advances us and the organization.
  
  

AI & Technical Fluency

• Work directly with APIs, data pipelines, and AI models to shape and validate solutions.
  
  
• Partner with engineers to design and ship AI-driven tools that fit seamlessly into existing workflows.
  
  
• Establish best practices for evaluating tools — weighing accuracy, usability, and long-term fit.
  
  
• Stay current on AI capabilities and help translate them into practical applications inside the client’s environment.
  
  

Culture & Excellence

• Raise the bar for product craft, from clear scopes to clean communication and transparent evaluations that anyone can quickly understand.
  
  
• Codify lessons into playbooks so the client builds lasting product capability.
  
  
• Build a culture of excellence: sharing wins, measuring outcomes, celebrating progress, and owning areas of improvement.
  
  

Minimum qualifications

• 8+ years of product management experience, ideally building tools for complex workflows or mission-critical environments.
  
  
• Proven ability to balance discovery and delivery — finding the right problems and shipping solutions that stick.
  
  
• Experience leading small engineering teams or pods with high accountability.
  
  
• Consulting mindset: able to embed inside client organizations, guide practices, and earn trust quickly.
  
  
• Excellent communicator who can flex for end users, engineers, and executives.
  
  
• Comfortable working with APIs and data pipelines — able to shape requirements, validate inputs, and build against structured data.
  
  

• Experience with modern data platforms, ideally Snowflake (or equivalent warehouses like BigQuery, Redshift).
  
  
• Able to make smart build choices with AI — knowing when to call APIs, when to use custom GPTs, and how to combine them into solutions that actually work for teams.
  
  
• Operates confidently in cloud environments, especially Microsoft Azure and AWS ecosystems.
  
  
• Bonus: familiarity with enterprise integrations (e.g. Tableau) to connect insights into user workflows.
  
  
• Above all, be someone that people admire, because you’re having fun doing great work.
  
  

Why this role is different

Most product roles optimize features in a SaaS app. This one is about embedding with real teams across architecture, engineering, and construction, understanding how they work, and building AI-powered tools that change how projects get designed and delivered in the real world. You’ll see your work land quickly, and you’ll set the playbook for how we approach product for years to come. 

Equal Opportunity Commitment

Human Agency is an Equal Opportunity Employer. We value diverse backgrounds and strive to build an inclusive culture where everyone feels welcomed and empowered.

WHAT WE DO

Our Data and Analytics consultants work with clients at all levels of the organization, from the C-suite to the shop floor, helping them to deliver on their most strategic initiatives. We’re known for making realistic, data-driven decisions that deliver value in tangible ways to our clients. Our clients ask for us on projects that require a superior combination of technical and business capabilities, people and management skills, and a collaborative mindset. We excel in understanding complex programs and strategic initiatives and breaking them into actionable pieces.

We are actively looking for professionals in the following areas:

• Data Strategy
• Data Governance
• Data Modernization
• Advanced Analytics
• Data Visualization

The ideal candidate’s experience may include but is not limited to the following:

• Have experience understanding and solving real business problems
• Have experience with presenting business case and strategy to the C-Suite
• Bring industry domain knowledge for custom data and analytics strategies
• Experience in designing and implementing data driven products and services
• Experience in designing and building high performance collaborative business and technology teams that deliver high value data solutions, data products and data analytics

Ideal candidates may call themselves Data Architects, Data Engineers, Data Scientists, Analysts and Data Governance professionals. Experience may include but not limited to the following:  

Data Strategy and Governance

• Intimately familiar with data technologies, data architecture frameworks, cloud platforms and the emerging trends in technological advancements.
• Proven experience in transforming our clients from on-prem data platforms to the cloud.
• Lead data modernization initiatives that include platform, technology and tools implementation and adoption.
• Must have experience in architecting and implementing data architecture, data engineering, reporting and analytical solutions across multiple business functions and domains.
• Conduct data management maturity assessments and identify pain points for including data quality, governance, architecture, analytics, metadata management, master data management.
• Demonstrate a rigorous and analytical problem-solving approach, leading information-gathering sessions and preparing and delivering client presentations and work products/prototypes.
• Identify data governance gaps and assess data governance maturity in a complex data environment. Should also be able to Identify the implications for data governance that arise from the technology, current processes, and skill levels in a complex data environment.

Data Architecture and Engineering

• Extensive experience or knowledge of cloud-based data platform technologies such as AWS, Microsoft Azure or Google Cloud Computing.
• Experience designing and building data platforms that support data lakes, data stores, data ingestion and transformations and API services for consuming data
• Ability to design and build complex data pipelines that either stream data in
• Experience and knowledge of programming and scripting languages, such as but not limited to Python, Node.JS and SQL
• Experience and knowledge of data integration tools and platforms
• Experience and knowledge of relational and dimensional database structures, theories, principles, and practice used in data warehousing and analytics solutions
• Ability to design and build data models using the appropriate technics to meet business objectives
• In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies.

Advanced Analytics and Data Visualizations

• Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire
• Experience with statistical and mathematical modeling, artificial intelligence and machine learning software and methods
• Experience and knowledge of programming and scripting languages such as, but not limited to, SQL, Python and R
• Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep
• Experience and knowledge of relational and dimensional database structures, theories, principles, and practice used in data warehousing and analytics solutions
• Experience deploying enterprise-wide reporting solutions while leveraging data visualization best practices

A career at SEI extends well beyond providing great service and thought leadership to our clients. Everyone takes an active role in building and managing our business, in an environment that runs counter to traditional consulting firms. Our consultants have a “seat at the table” and contribute to growing our business in ways that align to their interests such as growing business development opportunities, conducting interviews to support our hiring process, managing internal initiatives that build our brand or organizing trainings to share what you know with your colleagues. There is no telling what an SEI Consultant will be asked to do on a day-to-day basis – we do what it takes to get the job done.

QUALIFICATIONS

Required-

• Alignment to our core values: Excellence, Participation, Integrity and Collaboration
• Hungry, Humble, Smart
• Demonstrated business and technology acumen
• Strong written and verbal communication skills
• Understanding and experience solving real business problems
• Proven track record of delivering results
• Experience working with and/or leading a team
• Ability to work across industries, roles, functions & technologies
• Authorization for permanent employment in the United States (this position is not eligible for immigration sponsorship)

Preferred-

• Bachelor’s degree
• 8+ years professional experience
• Experience across our service offerings