Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Before Stripe, every growing internet platform had a payments team. Today, every growing internet platform has an Identity team. Identity verification has become core economic infrastructure for online businesses — enabling them to digitally verify their users' identities for fraud prevention, regulatory compliance, and trust and safety purposes.

At Stripe, we're building something more ambitious than a verification product. Our vision is to build the world's most trusted store of verified identities — a single, global, reusable, risk-scored representation of every individual who interacts with Stripe and beyond. This Identity Store becomes a platform with compounding network effects: more verifications enrich the store; a richer store produces better fraud signals; better signals mean lower friction for trusted users; lower friction drives more adoption.

Our product today serves millions of verifications per month for customers like OpenAI, Shopify, and WhatNot, and powers identity verification across multiple internal Stripe products including Fraud, Link, Connect, and Crypto. The problems ahead — adversarial AI and deepfake defense, networked identity infrastructure, progressive verification platforms, and low friction KYC APIs — sit at the frontier of what's possible in identity engineering.

What you’ll do

As a Staff Engineer on the Identity team, you will own the technical direction of one of Stripe's most strategically important product areas. This is not a role defined by task execution — it's a role defined by technical judgment, architectural influence, and the ability to turn an ambitious vision into a reliable, scalable system.

Responsibilities

• Own technical strategy — Define the architecture for Identity's core systems (Identity Store, headless verification platform, fraud detection infrastructure), make build-vs-buy-vs-partner decisions, and surface technical risks before they become customer-facing failures
• Lead 0-1 platform development — Architect net-new systems including the Identity Store, Networked Identity platform, and advanced fraud detection pipeline (behavioral biometrics, deepfake discriminators, adversarial training). Drive the evolution from a hosted-UI product to a headless-API and embedded-components platform
• Drive cross-functional alignment — Be the primary technical voice in roadmap and resourcing discussions. Partner with ML, product, legal, and engineering leads across Risk, Fraud, Link, Connect, and Crypto to ensure Identity's abstractions serve the full breadth of Stripe's product surface
• Raise the technical bar — Set engineering standards across ML, backend, mobile, and front-end; lead design reviews; and mentor senior engineers on the judgment needed to operate a high-stakes, externally-facing product
• Operate with ownership — Be accountable for reliability, scalability, and security of the systems you design — including the observability and alerting that catch model drift and fraud pattern shifts before customers do

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of software engineering experience, including 5+ years of experience in a strategic technical leadership role.
• Experience leading engineering team(s) working on API design, abstractions, frameworks, or client libraries (e.g. building internal or external developer products). 
• Proven track record of delivering pragmatic solutions that accelerate business growth 
• Ability to adjust conversations from high-level discussions to detailed coding 
• Thrives on a high level of autonomy and responsibility 
• Clear and persuasive writing and in-person communication 
• Strong problem-solving skills, critical thinking, determination, and a growth mindset 
• Ability to work effectively with a diverse group of people, genuinely caring for each other and contributing to high level of psychological safety for all team members and partner
• Has experience in a range of software languages and frameworks. Examples of what we work with include:
• Languages: primarily Ruby and Typescript, but also Python, Scala, Java, Go, and SQL (Spark and Trino dialects)
• Frameworks: React, GraphQL Kafka, Protobuf, Airflow, Bazel, Temporal, 
• Others: Mongo, Splunk, Prometheus

Preferred qualifications

• Experience with identity verification, fraud detection, or trust and safety systems — especially systems with adversarial inputs at scale
• Familiarity with ML systems in production: model serving, training pipelines, observability, drift detection, and the feedback loops that keep models accurate under adversarial conditions
• Experience building platform products with multiple consumer types — internal platform teams and external developers — where API backward compatibility and abstraction quality are first-class concerns
• Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorly
• Exposure to the technical stack we work with: primarily Ruby and TypeScript on the backend and web, Python for ML and data pipelines, with infrastructure spanning Kafka, Temporal, Protobuf, React, and distributed data stores
• Experience navigating ambiguity in a fast-moving organization — you can make confident technical decisions with incomplete information and update gracefully when new constraints emerge

Why Stripe Identity

• The market is at an inflection point. The global identity verification market is growing at ~15% CAGR, from $12.5B in 2024 to $21.8B by 2028. Competitors have more features today — but none of them have Stripe's moat: payments signals, fraud network, consumer graph, and KYC data spanning the full financial ecosystem. We're building to win the next decade, not the last one.
• The problems are genuinely hard. Adversarial ML against deepfakes and face swaps. Distributed identity graph architecture with real-time freshness requirements. Progressive verification APIs that minimize friction without sacrificing fraud detection accuracy. These are unsolved problems — not just at Stripe, but in the industry.
• You'll work on systems that matter immediately. The verifications we run protect real users from real fraud. When our recall improves by 10 points, that's millions of dollars in prevented fraud losses for customers who rely on us. When our mobile SDK completion rate rises, thousands more legitimate users successfully onboard each month.
• The team is small enough that your judgment shapes the architecture. This isn't a role where you inherit decisions made five years ago. It's a role where the decisions you make in 2026 are the ones the team will build on through 2029.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About this role

We are looking for an experienced Senior Business Intelligence Analyst to scale a critically important function responsible for building and maintaining systems, processes and services that enable us to understand financial performance and unlock key business insights at Faire. The ideal candidate for this role will ensure key accounting procedures are automated in ways that are accurate, efficient, easy-to-understand, and scalable. This role will sit in the Finance department and collaborate with team members from a breadth of functional groups across Faire, including Accounting, Finance & Strategy, Engineering and Data Infrastructure. This role will have a tremendous impact on the ability for Faire employees to use data effectively in order to report numbers externally and make impactful decisions internally. As an early member of a burgeoning team, you will have the opportunity to write the roadmap for how we improve access to business critical data and unlock automation that amplifies the impact of a variety of functions. 

What you’ll do 

• Scope, design, create, and manage complex ETL flows that aggregate and synthesize key business performance metrics and financial reporting, ensuring efficient, accurate, and scalable data models using best practices 
• Act as a trusted analytical partner to the Accounting and Finance teams providing technical expertise, gathering requirements from product and operational teams, and enabling data-driven decision-making and accountability by ensuring core ledgers accurately reflect business changes 
• Collaborate closely with Engineering, Data Infrastructure, and other stakeholders as a key translator and process improver, gathering requirements and delivering impactful data solutions that ensure alignment and efficiency across the organization 
• Lead initiatives to drive data strategy, roadmap planning, and prioritization, ensuring alignment with business objectives 
• Act as a thought leader to expand the team’s influence and impact throughout the Finance team and the broader organization 
• Drive workflow automation and innovation across Finance, including identifying and implementing Gen-AI–enabled productivity solutions to modernize processes and increase team leverage

Qualifications

• 5+ years of work experience in Business Intelligence, Analytics Engineering, Data Analytics, or comparable function 
• Expert in SQL with focus on data modeling, large-scale data processing, and tool development for analytics or Financial use cases. 
• Experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms 
• Experience with analytics workflow tools (examples: Airflow, Docker, dbt), data warehousing and storage (examples: Snowflake, BigQuery, Redshift, S3), and data visualization tools (examples: Mode, Tableau, Looker) 

Nice to have: 

• Experience with Python, R or other programming languages 
• BA/BS degree, ideally in computer science, math or another quantitative field 
• Familiarity with version control using Git and proficiency in command-line tools for workflow automation and data manipulation

Salary Range

San Francisco and New York: The pay range for this role is $174,500 to $240,000 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 POSITION
Our roster has an opening with your name on it

FanDuel is looking for a Senior Data Governance Analyst to drive data literacy across FanDuel.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

• Should Represent the Data Governance team in discussions with technical and business stakeholders globally as a subject matter expert on our toolkit and roadmap
• Support metadata management processes and standards across all of the data domains to ensure data integrity and standardization
• Promote a culture of data governance by developing partnerships with data owners and stewards to promote data governance best practices
• Outline and help implement data governance performance and standards, while developing and implementing operating plans to achieve those standards via audits, automation and processes
• Identify and communicate improvements in the design and effectiveness of key controls and processes including automation
• Serve as a SME on product interface and capabilities for select data domains
• Understand business requirements, translating them into actionable specifications including how data should be governed

THE STATS
What we're looking for in our next teammate

• BA or BS in Information Systems, CS, Data Management or Analysis or similar is desired.
• 5+ years’ experience in a data driven function and role such as a data governance analyst, quality assurance analyst, product owner, data analyst, or similar role diligently applying principles, practices, and theory
• Strong sense of ownership over deliverables, as this role will have end-to-end responsibilities for certain processes and procedures
• Good skills and knowledge of facilitation, situational awareness, conflict resolution, continual improvement, empowerment, and increasing transparency.
• Excellent written and verbal communication skills. Able to communicate anywhere from the team level to C-level executives.
• Excellent collaboration skills and the ability to communicate business value and obtain buy-in for process and culture changes

Preferred:

• Minimum two years of experience in the technology industry, knowledge of clickstream datasets a plus.
• Experience with Data Governance tools such as Alation, Collibra, Informatica, etc.
• Experience with Data Quality tools and/or Data Classification tools
• High familiarity with data platforms and applications such as S3, Databricks, Snowflake, Redshift, Airflow and BI Tools such as Tableau, Looker, Microstrategy
• Proficiency with Python, Pyspark or SQL
• Knowledge of sports and/or experience working within a heavily regulated industry is a plus
• Don’t check all the boxes? That’s okay! We encourage you to still apply if you feel like you possess an adjacent skill set and are interested in learning more about this position.
  
  

ABOUT FANDUEL

FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.  

In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

PLAYER BENEFITS
We treat our team right

We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here: FanDuel Total Rewards. *Benefits differ across location, role, and level.

FanDuel is an equal opportunities employer and we believe, as one of our principles states, “We are One Team!”. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.

The applicable salary range for this position is $138,000 - $181,650 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.

FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email Benefits@fanduel.com.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

#LI-Hybrid 

THE POSITION
Our roster has an opening with your name on it

FanDuel is looking for a Senior Data Governance Analyst to drive data literacy across FanDuel.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

• Should Represent the Data Governance team in discussions with technical and business stakeholders globally as a subject matter expert on our toolkit and roadmap
• Support metadata management processes and standards across all of the data domains to ensure data integrity and standardization
• Promote a culture of data governance by developing partnerships with data owners and stewards to promote data governance best practices
• Outline and help implement data governance performance and standards, while developing and implementing operating plans to achieve those standards via audits, automation and processes
• Identify and communicate improvements in the design and effectiveness of key controls and processes including automation
• Serve as a SME on product interface and capabilities for select data domains
• Understand business requirements, translating them into actionable specifications including how data should be governed

THE STATS
What we're looking for in our next teammate

• BA or BS in Information Systems, CS, Data Management or Analysis or similar is desired.
• 5+ years’ experience in a data driven function and role such as a data governance analyst, quality assurance analyst, product owner, data analyst, or similar role diligently applying principles, practices, and theory
• Strong sense of ownership over deliverables, as this role will have end-to-end responsibilities for certain processes and procedures
• Good skills and knowledge of facilitation, situational awareness, conflict resolution, continual improvement, empowerment, and increasing transparency.
• Excellent written and verbal communication skills. Able to communicate anywhere from the team level to C-level executives.
• Excellent collaboration skills and the ability to communicate business value and obtain buy-in for process and culture changes

Preferred:

• Minimum two years of experience in the technology industry, knowledge of clickstream datasets a plus.
• Experience with Data Governance tools such as Alation, Collibra, Informatica, etc.
• Experience with Data Quality tools and/or Data Classification tools
• High familiarity with data platforms and applications such as S3, Databricks, Snowflake, Redshift, Airflow and BI Tools such as Tableau, Looker, Microstrategy
• Proficiency with Python, Pyspark or SQL
• Knowledge of sports and/or experience working within a heavily regulated industry is a plus
• Don’t check all the boxes? That’s okay! We encourage you to still apply if you feel like you possess an adjacent skill set and are interested in learning more about this position.
  
  

ABOUT FANDUEL

FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.  

In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

PLAYER BENEFITS
We treat our team right

We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here: FanDuel Total Rewards. *Benefits differ across location, role, and level.

FanDuel is an equal opportunities employer and we believe, as one of our principles states, “We are One Team!”. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.

The applicable salary range for this position is $138,000 - $181,650 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.

FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email Benefits@fanduel.com.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

#LI-Hybrid 

About the Opportunity 

Managing data is a core element of operating the world’s most inspiring Virtual Power Plant (VPP). (You can’t fact check vibes.) Data Engineering is the team that brings it all together. From millions of internet-connected devices that use, store, and distribute power to all the clients that use those devices to manage grid load, Data Engineering makes it possible. We love data, translation, observability, and quality. 

From schema design to data transformation, from privacy and security to compliance, Data Engineering covers a lot of range. It’s a tight-knit team of engineers dedicated to excellence, quality, high-throughput communication, and deep collaboration. Client experience is at the focus of our efforts, but we also serve other internal customers with high-value data and information. 

The Role

You will integrate with the Data Engineering team, collaborating as a full-fledged member of the team, not doing some intern project on the side. You are joining us during the busiest season and will get a full glimpse of what it is like to work on a dedicated team of professionals who care about one another and are dedicated to each other’s success.

• Collaborate closely across teams to help build and maintain EnergyHub’s core data products
• Pair with and receive mentorship from brilliant engineers from a variety of backgrounds, gaining wisdom from their unique experiences and talents
• Deepen your knowledge of modern data engineering tools like Snowflake, dbt, Airflow, and Sigma
• Work in an agile environment, deepening your understanding of translating business and client needs into excellent products
• Contribute to mission-critical projects across the data lifecycle through
  • Feature development
  • Data platform enhancement
  • Bug fixes (identification & resolution)
  • Automations & efficiency improvements
  • Pair programming and code review (providing & receiving feedback)
  • Documentation
  • Monitoring and alerting
• Improve monitoring, troubleshooting, and resolution processes to improve our processes
• Monitor cloud costs across our toolset to maintain efficiency and justify expenses
• Build the absolutely coolest stuff of your career (so far)
• Help your hiring manager sustainably manage their usage of adjectives and adverbs
• Other duties as assigned

About you

• First and foremost, you have to sincerely love data and all the things it can enable and empower
• Current enrollment in (or immediate graduate of) an undergraduate or graduate program in or related to data engineering
• Proficiency in SQL and Python and perhaps even dbt and Sigma experience, with an awesome ability to bring sanity and clarity to syntactic complexity
  • Nice to have: Snowflake Data Warehousing Workshop (Badge 1)
  • Nice to have: dbt Fundamentals
• Some monitoring and dashboarding experience (e.g. Snowflake, Sigma, Datadog)
• A clear understanding of the difference between OLAP and OLTP RDBMS systems and when to recommend one over the other
• Knowledge of a variety of file structures such as CSV, JSON, and Parquet, and when one might be preferable over others
• Drive and dedication for quality and performance in everything you touch and thirst for learning new techniques
• Clear communication (written and verbal), capable collaboration (in-office and online), and cultivated curiosity
• Warmth and welcoming for your collaborators, colleagues, and cohort, with an urge to help them succeed and pay their generosity forward to others
• Above-average appreciation for alliteration
• Well-grounded stance on AI adoption that makes you a stronger, more capable engineer

Please note that sponsorship of new applicants for employment authorization, or any other immigration-related support, is not available for this position at this time.

Why work for EnergyHub?

• Collaborate with outstanding people: Our employees work hard, do great work, and enjoy collaborating and learning from each other.
• Gain well rounded experience: EnergyHub offers a diverse and dynamic environment where you will get the chance to work directly with executives and develop expertise across multiple areas of the business.
• Work with the latest technologies: You'll gain exposure to a broad spectrum of IoT, SaaS and machine learning obstacles, including distributed fault-tolerance, device control optimization, and process modeling to support scalable interaction with disparate downstream APIs.
• Be part of something important: Help create the future of how energy is produced and consumed. Make a positive impact on our climate.

About EnergyHub

EnergyHub empowers utilities and their customers to create a clean, distributed energy future. We help consumers turn their smart thermostats, EVs, batteries, and other products into virtual power plants that keep the grid stable and enable higher penetration of solar and wind power.

To learn more, visit energyhub.com.

EnergyHub is an Equal Opportunity Employer

EOE, Including Disability/Vets. Reasonable accommodations are available for individuals with disabilities throughout the application process. If you are a person with a disability needing assistance with the application process, please contact accommodations.apply@energyhub.net.

In connection with your application, we collect information that identifies, reasonably relates to or describes you ("Personal Information"). The categories of Personal Information that we may collect include your name, government-issued identification number(s), email address, mailing address, other contact information, emergency contact information, employment history, educational history, and demographic information. We collect and use those categories of Personal Information about you for human resources and other business management purposes, including identifying and evaluating you as a candidate for potential or future employment or future positions, recordkeeping in relation to recruiting and hiring, conducting analytics, and ensuring compliance with applicable legal requirements and Company policies. By submitting your application, you acknowledge that we may retain some of the personal data that you provide in your application for our internal operations such as managing our recruitment system and ensuring that we comply with labor laws and regulations even after we have made our employment decision.

Notice To Third Party Agencies:

EnergyHub understands the value of professional recruiting services. However, we are not accepting resumes from recruiters or employment agencies for this position. In the event we receive a resume or candidate referral for this position from a third-party recruiter or agency without a previously signed agreement, we reserve the right to pursue and hire those candidate(s) without any financial obligation to you.

About the Opportunity

The Commercial & Industrial (C&I) Team facilitates the management of our non-residential demand response programs, covering some of our largest customers and programs by flexible grid capacity. Our newly formed team will play a critical role in ensuring the scalability and flexibility of our future by creating a first class platform for our clients. This is an opportunity to join a highly energized team of engineers eager to define and develop key concepts, solve complex challenges with real-world constraints and have a positive impact on our climate future. This is a three-month internship opportunity.

Main Responsibilities: What you’ll do

• Collaborate with and receive mentorship from brilliant engineers from a variety of backgrounds, gaining wisdom from their unique experiences and talents
• Own a high-impact project during your internship and deepen your knowledge of modern data engineering tools like Snowflake, dbt, Airflow, and Sigma
• Work in an agile environment, deepening your understanding of translating product requirements into excellent products
• Improve monitoring, troubleshooting, and resolution processes to improve EnergyHub’s products
• Improve our production pipelines, reducing tech debt and ensuring efficient data processing for our customers
• Other duties as assigned

Required Skills and Experience: What you need

• First and foremost, you have to sincerely love data and all the things it can enable and empower
• Current enrollment in (or immediate graduate of) an undergraduate or graduate program in or related to data engineering
• Proficiency in SQL and Python and perhaps even dbt and Sigma experience, with an awesome ability to bring sanity and clarity to syntactic complexity
• Some monitoring and dashboarding experience (e.g. Snowflake, Sigma, Datadog)
• A clear understanding of the difference between OLAP and OLTP systems and a basic familiarity with file structures like CSV, JSON, and Parquet.

Preferred Skills and Experience: Nice-to-haves

• Drive and dedication for quality and performance in everything you touch and thirst for learning new techniques
• Clear communication (written and verbal), capable collaboration (in-office and online), and cultivated curiosity
• Warmth and welcoming for your collaborators, colleagues, and cohort, with an urge to help them succeed and pay their generosity forward to others

Please note that sponsorship of new applicants for employment authorization, or any other immigration-related support, is not available for this position at this time.

Why work for EnergyHub?

• Collaborate with outstanding people: Our employees work hard, do great work, and enjoy collaborating and learning from each other.
• Gain well rounded experience: EnergyHub offers a diverse and dynamic environment where you will get the chance to work directly with executives and develop expertise across multiple areas of the business.
• Work with the latest technologies: You'll gain exposure to a broad spectrum of IoT, SaaS and machine learning obstacles, including distributed fault-tolerance, device control optimization, and process modeling to support scalable interaction with disparate downstream APIs.
• Be part of something important: Help create the future of how energy is produced and consumed. Make a positive impact on our climate.

About EnergyHub

EnergyHub empowers utilities and their customers to create a clean, distributed energy future. We help consumers turn their smart thermostats, EVs, batteries, and other products into virtual power plants that keep the grid stable and enable higher penetration of solar and wind power.

To learn more, visit energyhub.com.

EnergyHub is an Equal Opportunity Employer

EOE, Including Disability/Vets. Reasonable accommodations are available for individuals with disabilities throughout the application process. If you are a person with a disability needing assistance with the application process, please contact accommodations.apply@energyhub.net.

In connection with your application, we collect information that identifies, reasonably relates to or describes you ("Personal Information"). The categories of Personal Information that we may collect include your name, government-issued identification number(s), email address, mailing address, other contact information, emergency contact information, employment history, educational history, and demographic information. We collect and use those categories of Personal Information about you for human resources and other business management purposes, including identifying and evaluating you as a candidate for potential or future employment or future positions, recordkeeping in relation to recruiting and hiring, conducting analytics, and ensuring compliance with applicable legal requirements and Company policies. By submitting your application, you acknowledge that we may retain some of the personal data that you provide in your application for our internal operations such as managing our recruitment system and ensuring that we comply with labor laws and regulations even after we have made our employment decision.

Notice To Third Party Agencies:

EnergyHub understands the value of professional recruiting services. However, we are not accepting resumes from recruiters or employment agencies for this position. In the event we receive a resume or candidate referral for this position from a third-party recruiter or agency without a previously signed agreement, we reserve the right to pursue and hire those candidate(s) without any financial obligation to you.

About the team + role

We are looking for an intellectually curious and enthusiastic individual to help the organization prepare for continued rapid growth by having a good understanding of the impact of the financial markets and risks on Robinhood. This role is responsible for monitoring corporate liquidity risks and investments, developing financial risk models, forecasting key balance sheet items and providing deep dive analysis into financial market drivers of the business.

This role suits those with a bias towards action and impact, who believe in end to end execution and accountability. You are the perfect mix of analytical, technical, operational, and creative. You are a clear, confident communicator who loves taking a complicated problem, decomposing it, and building data driven models, then turning those models into processes and reports. 

What you’ll do

• Monitor and report on financial risks across the firm on a daily basis, ensuring timely escalation of material exposures
• Conduct deep-dive quantitative analyses into liquidity risks emerging across the Robinhood ecosystem   
• Enhance and maintain liquidity risk models and forecasting frameworks to support proactive risk management
• Partner with Data Science and Engineering teams to design and deliver dashboards, automated alerts, and data pipelines that surface capital, liquidity, and counterparty credit risks for the Treasury function
• Collaborate with Finance and Product teams to assess emerging risks associated with new products and business initiatives

What you bring

• Bachelor's degree in mathematics, computer science, engineering or a related field.
• 1–3 years of experience in data analytics, risk management, or a comparable analytical role
• Strong quantitative and problem-solving skills, with the ability to communicate complex findings clearly to non-technical stakeholder
• Solid grounding in financial risk methodologies including Value-at-Risk, stress testing, scenario analysis, and attribution modeling
• Understanding of macroeconomics, financial markets, financial instruments, trading strategies, and investment theory
• Advanced proficiency in SQL and Python
• Ability to build and own process from the ground up
• Demonstrated ability to design and own end-to-end processes in ambiguous, fast-moving environments

Bonus points:

• Advanced graduate degree such as an MFE or in a similar technical field preferred.
• Experience developing and deploying production-grade financial models in Python or R
• Familiarity with sophisticated financial instruments including derivatives, futures, leveraged products, and digital assets
• Experience with time series modeling and regression techniques
• Hands-on experience with AI/ML tooling and business intelligence platforms such as Superset or Looker
• Working knowledge of ETL pipelines and workflow orchestration tools such as Airflow

As a Senior Analyst, Analytics engineering, you’ll enable our analytics community to get the most out of our data. You’ll support analysts of varying levels of scope and experience by building, maintaining, and governing a data warehouse of operational and financial data.

You’ll keep us on the cutting edge of AI-driven analytics by partnering with Data Ops to develop a semantic layer and various agents to facilitate faster, better, and more interpretable insights.

We're seeking someone based near one of the following cities: San Francisco, Salt Lake City, Chicago, or New York City.

RESPONSIBILITIES

• Develop and maintain data models in Snowflake with dbt
• Design and build a testing and alerting framework to improve data quality
• Create data governance/democratization policies to support the broader analyst community
• Design and build a self-service analytics AI framework, including both the semantic modeling and tooling architecture

Partner with Data Engineering to optimize data staging in Snowflake

QUALIFICATIONS 

• 4+ years of experience in data engineering, analytics, or data science
• A bachelor’s degree in Computer Science, Information Systems, Statistics, or another quantitative field
• Advanced SQL knowledge (experience with dbt is a plus)
• Moderate Python knowledge (JavaScript knowledge is a plus)
• Experience building complex data pipelines using engineering best practices in platforms like Airflow or Prefect

Strong organizational discipline and quality assurance skills

PERKS & BENEFITS 

• We offer Gongsters a variety of medical, dental, and vision plans, designed to fit you and your family’s needs.
• Wellbeing Fund - flexible wellness stipend to support a healthy lifestyle.
• Mental Health benefits with covered therapy and coaching.
• 401(k) program to help you invest in your future.
• Education & learning stipend for personal growth and development.
• Flexible vacation time to promote a healthy work-life blend.
• Paid parental leave to support you and your family.
• Company-wide recharge days each quarter.
• Work from home stipend to help you succeed in a remote environment.

The annual salary hiring range for this position is $120,000 - $145,000 USD. 

Compensation is based on factors unique to each candidate, including, but not limited to, job-related skills, qualification, education, experience, and location. At Gong, we have a location-based compensation structure, which means there may be a different range for candidates in other locations. The total compensation package for this position, in addition to base compensation, may include incentive compensation, bonus, equity, and benefits. Some of our sales compensation programs also offer the potential to achieve above targeted earnings for those who exceed their sales targets. 

We are always looking for outstanding Gongsters! So if this sounds like something that interests you regardless of compensation, please reach out. We may have more roles for you to consider and would love to connect.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Gong recruiting email communications will always come from the @gong.io domain. Any outreach claiming to be from Gong via other sources should be ignored.

Gong is an equal-opportunity employer. We believe that diversity is integral to our success, and do not discriminate based on race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, military status, genetic information, or any other basis protected by applicable law.

To review Gong's privacy policy, visit https://www.gong.io/gong-io-job-candidates-privacy-notice/ for more details.

#LI-NK1

At Scale AI, we help leading enterprises turn AI from a promising capability into reliable systems that improve real workflows and deliver measurable business value. We are hiring a Senior Forward Deployed Data Scientist / Engineer to work directly with customers on ambiguous, high-impact problems at the intersection of data science, product development, and AI deployment.

This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production. In many cases, the data scientist builds the first usable version of the solution, proves value quickly, and helps drive it into a durable product or platform capability.

The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.

What you’ll do

• Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria
• Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans
• Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems
• Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration
• Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations
• Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement
• Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline
• Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production
• Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities

What we’re looking for

• 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role
• Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact
• Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans
• Strong foundation in statistics, experimentation, causal reasoning, and measurement
• Experience building tools or products, not just analyses — for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications
• Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect data, prototype quickly, debug deeply, and productionize solutions that work
• Comfort using AI-assisted coding and development workflows to move from idea to usable product quickly
• Strong communication and stakeholder management skills; able to work effectively with customers, engineers, product teams, and executives
• High ownership and bias toward shipping in fast-moving environments with incomplete information

Preferred qualifications

• Experience in a forward deployed, solutions, consulting, or other client-facing technical role
• Experience designing evaluation frameworks for LLMs, retrieval systems, agentic workflows, or other AI-enabled products
• Experience with large-scale data processing and distributed systems such as Spark, Ray, or Airflow
• Experience with cloud infrastructure and modern data platforms such as AWS, GCP, Snowflake, or BigQuery
• Experience building lightweight applications, APIs, internal tools, or workflow software on top of data/ML systems
• Familiarity with marketplace experimentation, causal inference, forecasting, optimization, or advanced statistical modeling
• Strong product instinct and the judgment to know when the right answer is a model, an experiment, a tool, or a workflow redesign

What success looks like

Success in this role means taking a messy, high-stakes customer problem and turning it into a deployed system that is actually used. Sometimes that system is a model. Sometimes it is an evaluation framework. Sometimes it is an operator-facing tool or a lightweight data product that changes how decisions get made. In all cases, success is defined by measurable impact, rigorous evaluation, and reliable execution.

About the Role

As an Analytics Engineer, you will be an early member of the Data Science & Analytics team building the foundation to scale analytics across our organization. You will collaborate with key stakeholders in Engineering, Product, GTM and other areas to build scalable solutions to transform data into key metrics reporting and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics that can scale with our company’s growth. You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions. 

Responsibilities:

• Understand the data needs of stakeholder teams in terms of key data models and reporting, and translate that into technical requirements
• Define, build and manage key data pipelines in dbt that transform raw logs into canonical datasets
• Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data
• Develop insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company
• Build foundational data products, dashboards and tools to enable self-serve analytics to scale across the company
• Influence the future roadmap of Product and GTM teams from a data systems perspective
• Become an expert in our organization’s data models and the company's data architecture

You might be a good fit if you have:

• 5+ years of experience as an Analytics Data Engineer or similar Data Science & Analytics roles, preferably partnering with GTM and Product leads to build and report on key company-wide metrics.
• A passion for the company's mission of building helpful, honest, and harmless AI.
• Expertise in building multi-step ETL jobs, building robust data models through tooling like dbt; proficiency with workflow management platforms like Airflow and version control management tools through GitHub.
• Expertise in SQL and Python to transform data into accurate, clean data models.
• Experience building data reporting and dashboarding in visualization tools like Hex to serve multiple cross-functional teams.
• A bias for action and urgency, not letting perfect be the enemy of the effective.
• A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
• Experience building an Analytics Data Engineering (or similar) function at start-ups. 
• A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.

Who We Are

EDO is the TV outcomes company. Our measurement platform connects convergent TV airings to the ad-driven consumer behaviors most predictive of future sales, helping advertisers, agencies, networks, streamers, and studios understand what works across linear and streaming TV.

We combine immediate engagement signals with decision science, vertical AI, and investment-grade data to help the advertising industry maximize media impact, optimize creative performance, and value every impression. EDO is headquartered in New York City and Los Angeles with office space in San Francisco. For employees residing full-time in NYC, SF, or LA, we have a hybrid work policy of three days in the office and two remote work days.

The Role

EDO is looking for a Senior Platform Engineer to help accelerate our shift toward a platform model. This is a senior IC role on the Infrastructure team focused on paved paths, reusable infrastructure patterns, and self-service workflows that help software, data, and machine learning engineers ship safely and efficiently.

Our environment is AWS-heavy and data-intensive, with heavy use of EC2, RDS, S3, SageMaker, MWAA/Airflow, Snowflake, dbt, Chef, Terraform, Spacelift, and emerging ECS/container patterns. The right person has strong AWS and infrastructure-as-code fundamentals, prior exposure to platform engineering practices, and the pragmatism to modernize existing systems without assuming everything should be rebuilt from scratch.

We approach infrastructure as an internal product: understanding engineers’ needs, prioritizing high-leverage platform capabilities, and iterating on tools and workflows that make teams faster, safer, and more self-sufficient.

What You Will Do

• Build and evolve EDO's internal platform capabilities: paved paths, reusable infrastructure modules, deployment standards, documentation, and self-service workflows.
• Own and improve Terraform and Spacelift-based infrastructure workflows, including module design, reviews, approvals, drift detection, and guardrails.
• Modernize existing AWS infrastructure, including EC2- and Chef-based systems, while helping teams adopt more standardized and repeatable patterns over time.
• Support production data and ML platform infrastructure, including MWAA/Airflow, Snowflake, dbt, SageMaker, S3, RDS, and related AWS services.
• Partner with software, data, and ML engineers as internal customers, turning recurring infrastructure needs into scalable platform capabilities rather than one-off support work.
• Improve deployment, CI/CD, observability, alerting, and incident response practices so teams can operate production systems with greater confidence.
• Expand pragmatic ECS/container deployment patterns where they create value, without treating Kubernetes as the default answer.
• Participate in a lightweight on-call rotation and use operational learnings to reduce toil, improve reliability, and strengthen the platform.

What We Are Looking For

• 6+ years of experience in platform engineering, infrastructure engineering, SRE, DevOps, cloud infrastructure, or similar roles.
• Experience building, operating, or contributing to an internal developer platform, infrastructure platform, developer productivity team, or similar platform-oriented function.
• Strong production experience with AWS, especially EC2, RDS, S3, IAM, networking, load balancing, and related operational patterns.
• Strong hands-on experience with Terraform or similar infrastructure-as-code tooling, including reusable modules and multi-environment patterns.
• Comfort working in a data-heavy environment and supporting technologies such as Airflow/MWAA, Snowflake, dbt, SageMaker, S3, and RDS.
• Product-minded approach to infrastructure: able to understand engineer pain points, prioritize high-impact platform work, document paved paths, and iterate based on adoption and feedback.
• Strong operational judgment, including debugging production systems, improving observability, and building platform patterns that support reliability, security, and cost efficiency.

Bonus Points

• Hands-on experience with Spacelift or similar IaC orchestration platforms such as Terraform Cloud or Atlantis.
• Experience helping an organization adopt platform engineering practices, including paved paths, golden paths, service templates, and developer-facing documentation.
• Experience with Chef, AWS cost management, security/compliance-driven infrastructure, or production ML/data science infrastructure.

Compensation and Benefits

EDO offers a competitive compensation package. Components of compensation include:

• Mid-stage equity and competitive salary
• Flexible Time Off
• Medical, dental and vision coverage: EDO provides full coverage for individual medical plans and partial coverage for dependent or family plans.
• 401(k) plan, FSA, HSA
• Commuter Benefits
• When in an office, employee meals, snacks, and more

In compliance with New York and California Pay Transparency Law, the salary range for this position is $170,000 to $190,000 plus equity. We note the salary information as a general guideline only, as actual compensation may vary from posting. We will consider various factors to determine the offer for this role, including the scope and responsibilities of the position, relevant work experience, key skills, training, and business considerations.

EDO is an Equal Opportunity Employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status. All your information will be kept confidential according to EEO guidelines.

The role:

As a Staff Full Stack Engineer, you will serve as a cornerstone of technical leadership, driving the ideation, architectural design, and optimization of enterprise-scale, full-stack ecosystems. We are seeking a visionary with 8+ years of engineering depth and a proven track record of delivering complex, end-to-end solutions. In this role, you will bridge the gap between high-level business strategy and technical execution, championing engineering excellence while serving as a pivotal mentor and subject matter expert to the broader engineering organization.

What you’ll do: 

Engineering & AI Architecture

• Architectural Leadership: Architect and deploy sophisticated, end-to-end applications, leveraging deep expertise in interactive interfaces and complex data integration—including the orchestration of AI-native database functions like Snowflake Cortex.
• Agentic AI Integration: Partner with AI specialists to architect multi-agentic systems, implementing autonomous, stateful workflows designed to solve high-consequence, real-world business challenges.
• Data Orchestration: Design and automate high-performance real-time and batch data pipelines using enterprise orchestration tools such as Apache Airflow, ensuring seamless data liquidity across the stack.

DevOps & Operational Excellence

• Infrastructure as Code (IaC): Standardize deployment lifecycles and cloud infrastructure by implementing GitOps methodologies via ArgoCD, GitLab CI/CD, and AWS best practices.
• Workflow Optimization: Deploy and tune complex business process engines within enterprise frameworks, ensuring maximum reliability, scalability, and observability.

Product Ownership & Strategy

• Technical Decomposition: Lead the translation of ambiguous product requirements into rigorous technical specifications, overseeing the entire execution lifecycle from initial ideation to post-deployment optimization.
• Strategic Collaboration: Act as a technical bridge between Product, Design, and Engineering to deliver member-centric solutions while fostering a culture of continuous learning and growth.

Governance & Innovation

• Technical Stewardship: Drive engineering rigor through comprehensive code and design reviews, serving as a final decision-maker for critical architectural choices and software standards.
• Innovation Advocacy: Maintain a cutting-edge pulse on GenAI, LLM infrastructure, and emerging tooling; proactively translating industry trends into actionable product roadmaps and enhanced technical capabilities.

What you’ll need:

Education & Experience

• Academic Foundation: Bachelor’s or Master’s degree in Computer Science, Engineering, or a strictly related technical discipline.
• Professional Tenure: 8+ years of robust software engineering experience, with a specialized focus on architecting full-stack AI-driven product ecosystems.
• Proven Reliability: A distinguished track record of delivering production-grade, highly available cloud services that operate reliably at enterprise scale.

Technical Mastery

• Full-Stack Command: Advanced proficiency in the React and Node.js ecosystems, with a mastery of seamless front-to-back-end integration for bespoke enterprise applications.
• Data & AI Infrastructure: Extensive hands-on experience with modern database platforms—Snowflake preferred—including the utilization of Snowflake Cortex and advanced AI/ML integration patterns.
• Pipeline Orchestration: Deep expertise in designing and managing complex real-time and scheduled data pipelines using Apache Airflow.
• DevOps & GitOps: Comprehensive experience in Infrastructure as Code (IaC) and environment management, utilizing ArgoCD and GitLab CI/CD to drive automated, resilient deployment strategies.

Leadership & Influence

• Strategic Mentorship: Committed to the growth of the engineering organization through active mentorship, fostering a high-performance culture, and elevating the technical caliber of the team.
• Operational Excellence: A relentless advocate for engineering rigor, consistently challenging the status quo to drive continuous improvement in code quality and architectural standards.
• Cross-Functional Diplomacy: Exceptional communication skills with the ability to bridge technical and non-technical domains, driving consensus and decision-making among diverse stakeholders.
• Organizational Catalyst: A proactive leader who takes end-to-end ownership, champions a culture of innovation, and builds influential partnerships across the broader engineering community.

Nice to have:

• Advanced AI & LLM Implementation: Direct experience deploying and scaling production-level Generative AI solutions, specifically LLM-powered agents or Retrieval-Augmented Generation (RAG) architectures.
• Sector Expertise: Previous background in Fintech or high-throughput consumer-facing environments, with an understanding of the unique security and regulatory nuances involved.
• Cloud Proficiency: Advanced experience with AWS ecosystem services and a broad familiarity with modern cloud-native orchestration platforms.
• Architectural Rigor: A sophisticated understanding of latency, throughput, and scalability trade-offs, with the ability to optimize complex distributed systems for performance.
• Computer Science Depth: Strong conceptual mastery of diverse programming paradigms, including Object-Oriented (OOP) and Functional Programming, to ensure clean, maintainable, and modular codebases.
• Evolving AI Ecosystems: Experience navigating and integrating emerging AI workflow orchestration tools and third-party AI research platforms.

The role:

As a Senior Full Stack Engineer, you will serve as a primary contributor in the development, deployment, and optimization of enterprise-grade, full-stack custom applications at scale. The ideal candidate brings 5+ years of robust engineering experience, a distinguished history of end-to-end delivery, and comprehensive mastery of software design—ranging from intricate user interfaces and business workflows to foundational back-end data architecture. You will collaborate with cross-functional teams to define technical strategy, advocate for engineering excellence, and deliver high-impact solutions directly to our member community.

What you’ll do: 

• Architect, design, and build end-to-end user-facing software applications using rich interactive user-interfaces with your expertise working with information extracted from databases and APIs (including leveraging native database functions such as Snowflake Cortex for advanced AI workloads).
• Manage deployment pipelines and infrastructure as code using ArgoCD, GitLab CI/CD, and AWS best practices.
• Collaborate with the AI engineers on the team to implement multi-agentic AI applications, enabling autonomous, stateful, and collaborative agent workflows for complex, real-world problem solving
• Own technical decompositions of new product requirements; lead delivery from ideation to deployment and continual improvement.
• Deploy, optimize, and monitor complex business process workflows on enterprise frameworks 
• Automate real-time and batch data flows using orchestration tools such as Apache Airflow.
• Participate in code and design reviews, and make technical decisions for design and architecture of software solutions.
• Collaborate with Product, Design, and Engineering to deliver high-impact solutions and foster a growth-mindset environment.
• Stay current with the latest trends in software engineering, GenAI, LLM infrastructure, and the evolving tooling ecosystem; generate ideas to expand product capabilities and technical reach.

What you’ll need:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 5+ years of professional software engineering experience, with a focus on full-stack frameworks and engineering to develop custom product delivery specializing in AI
• Solid devops and infrastructure-as-code experience using ArgoCD and GitLab for deployment, CI/CD, and environment management.
• Advanced proficiency in React, Node.js, and front-end–to–back-end custom app development.
• Extensive hands-on experience with database platforms - Snowflake strongly preferred, including advanced features, AI/ML integrations, and Snowflake Cortex.
• Deep expertise in orchestrating real-time and scheduled pipelines with Airflow.
• Track record of delivering high-quality, production-grade, scalable, and highly available cloud-based services.
• Strong communicator; able to collaborate and drive decision-making with cross-functional stakeholders.
• Willingness to take ownership, and champion learning and innovation within the organization.

Nice to have:

• Exposure to other cloud-native or AI workflow orchestration platforms.
• Experience with AWS
• Prior fintech or high-throughput consumer product experience.
• Experience deploying and scaling LLM-powered chatbots or retrieval-augmented generation (RAG) platforms.

About the Role

We’re looking for a Director of Engineering to lead our Intelligent Messaging group—one of the most critical and high-impact areas at Attentive. This team powers the systems behind billions of personalized messages (SMS, email, push) sent every month, helping the world’s leading brands connect with consumers in smarter, more meaningful ways.

At the core of this is AI, machine learning, and real-time data. This allows us to drive personalization at massive scale - turning every message into an opportunity to engage, convert, and build long-term customer relationships.

In this role, you’ll lead multiple teams and play a key role in defining how AI shapes the future of messaging at Attentive. You’ll partner closely with Product and Engineering leadership to build and scale systems that are fast, reliable, and deeply intelligent. You’ll stay close to the work - guiding architecture, unblocking complex problems, and stepping in when it matters - while also building strong teams and developing great managers.

This is a role for someone who likes to operate deep in the systems, close to the people, and aligned with the business. You’ll own the technical direction of a high-scale, high-uptime platform and help us push what’s possible as we continue to grow.

This is a hybrid role based in NYC, with occasional travel to our SF office.

What You’ll Accomplish

• You’ll own the delivery of cutting-edge, AI-powered consumer messaging experiences used by millions
• You’ll manage and evolve a multi-team organization, build on our great culture, and set a high bar for engineering excellence
• You'll oversee the technical strategy in multiple domains, supporting various layers of our messaging applications by using existing and emerging technology platforms
• You’ll accelerate our engineering velocity using cutting-edge agentic and LLM tooling, while successfully managing safety and stability
• You’lll collaborate with product, ML, design, and data science to shape the roadmap - not just execute on it
• You’ll work directly with partner teams and stakeholders in the platform, go-to-market, and customer success organizations

Your Expertise

• Above all else, you are technical and love to dive deep to understand architecture, code, and infrastructure. This is the most critical attribute for success at Attentive.
• You have 10+ years of industry experience, including managing teams of 30+ engineers, and at least 2 years managing managers. From a technical perspective, you have 8+ years of experience in software engineering roles, ideally reaching staff level as an individual contributor.
• You embrace agentic workflows, and understand the benefits, complexity and risks of the fast-moving AI ecosystem
• You care about software quality and have a track record of building reliable, high-uptime systems, particularly in data-intensive environments
• You’re comfortable operating in fast-moving, high growth environments, translating business needs into the right levels of implementation

What We Use

• Our backend is Java / Kotlin / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Aurora, AirFlow, Postgres, and Redis, hosted via AWS
• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS, using tooling like Istio, Datadog, Terraform, CloudFlare, and Helm
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, industry-leading LLMs, lots of data and tech like Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $250,000 - $350,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-EF1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

The opportunity
Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform also supports large-scale model training, feature generation, and experimentation workflows that power production ML systems.

To support this growth, we need strong technical ownership to ensure our ML pipelines remain reliable, scalable, and architecturally sound.

We are seeking a staff ML engineer to design and evolve the large-scale offline platform. This role focuses on building reliable infrastructure for generating training datasets, orchestrating ML workflows, and enabling efficient, distributed model training at scale. You will work closely with ML engineers and platform teams to ensure our pipelines can efficiently handle growing data volumes and increasingly complex training workloads.

You will play a key role in shaping how model datasets are prepared as well as model training, validated, and delivered to distributed training systems, while ensuring the reliability, scalability, and performance of our offline ML platform.

What you'll be doing

• Design and operate large-scale data pipelines that generate training datasets used for machine learning training and experimentation
• Develop infrastructure that supports distributed training workflows using technologies such as Pytorch, Ray Data, and Ray Train, etc.
• Integrate ML pipelines with workflow orchestration systems (e.g., Flyte, Airflow, or similar) to enable reliable multi-stage training workflows
• Improve reproducibility and observability of ML pipelines through dataset validation, monitoring, and automated testing
• Optimize performance and resource utilization across distributed compute systems used for data processing and model training
• Partner closely with ML engineers to enable efficient large-scale experimentation and model iteration
• Lead architectural improvements to ensure our offline ML pipelines remain scalable, reliable, and cost-efficient

What we're looking for

• Strong experience building large-scale ML pipelines
• Experience working with distributed computing frameworks such as Ray, Spark, Flink and familiarity in the Ray ecosystem (Ray Data, Ray Train) for distributed data processing and model training
• Experience building infrastructure for training data generation, dataset preparation, or ML feature pipelines
• Deep experience designing and operating production-grade data pipelines
• Strong programming skills in Python and experience working with large-scale distributed workloads
• Experience with modern data infrastructure (data lakes, warehouses, orchestration systems, streaming platforms)
• Strong systems thinking, with the ability to reason about performance, scalability, reliability, and cost tradeoffs in distributed systems
• Proven ability to lead technical direction and influence architectural decisions across teams without formal authority

Additional information

• Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#SEN #LI-ED1

About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

What You’ll Accomplish

• Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
• Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
• Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
• Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
• Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
• Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
• Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
• Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

• 7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
• Strong proficiency in one or more modern programming languages such as Java, or Typescript
• Experience designing and operating distributed systems, APIs, and microservice architectures at scale
• Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
• Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
• Track record of building reliable, scalable, high throughput systems that support customer facing products
• Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
• Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
• A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

About the Role:

The Data Platform Mission aims to empower the organization to access and use data to answer important questions, power user experiences, and to make strategic decisions that drive value and impact across the organization.

We are looking for Analytics Engineers that can help develop a new function within Data Platform that focuses on supporting our most critical data assets across The New York Times data domains. You will partner with many different teams and roles to develop data products, capabilities, and technologies. This role is based in our New York City office in Times Square.

As an Analytics Engineer II, you'll work with teams across the organization to manage, support, and improve the quality of data across specific organizational domains that help to make data-driven decisions and experiences as efficient as possible. You will develop deep expertise within specific data domains, being a subject matter expert for the business and being an important partner across data initiatives. You will report to the Executive Director of Analytics Engineering.

Responsibilities:

Data Platform Evangelist

• Provide frameworks, training, and guidance to individuals across the organization to utilize data platform capabilities or to submit well-defined data needs and requests
• Establish data management frameworks that provide clear recommendations and requirements for data producers, while also working with data platform team to integrate into capabilities
• Embed and work closely with data platform teams to build out governance into core capabilities

Data Quality

• Create and maintain data quality frameworks, definitions, and metrics that are consistently applied across data domains, products, and key data assets
• Define and test business logic to identify and surface domain-specific quality measures in conjunction with other data teams, that can be passed to data platform teams to implement once validated
• Establish a process to implement, track, and ensure data quality frameworks are adhered to
• Proactively monitor, surface, triage and track key data issues for data products and systems that provide visibility for data producers and data consumers to react accordingly, including the development of enterprise dashboards
• Partner with data engineering teams to test and build out capabilities that promote quality, including data lineage, testing frameworks, writing quality checks, etc.

Domain Support

• Maintain, update, and evolve our enterprise data and metrics catalogs
• Ensure the accuracy, completeness, consistency, and reliability of data within assigned domains
• Collaborate with various teams to understand domain needs, prioritize initiatives, maintain data models, and oversee the implementation of data governance standards
• Continuously improve data quality, identifies issues, and develops solutions to comply with regulatory requirements
• Document data management standards and supports business data stewards
• Identify and resolve data issues and risks within the domain
• Monitor domain maturity index with KPIs of data governance, quality, integration, security, and analytics
• Develop domain-specific documentation such as Data Use Cases and Data Flow Diagrams
• Provide support and training to the business regarding data governance and modeling

Analytics Enablement

• Work closely with data platform to pilot, test, and build out user-friendly ways to consume data products
• Collaborate with business stakeholders, Data and Insights teams, and Data Platform product managers to gather requirements and translate into effective, user-friendly dashboards, reports, datasets, or artifacts
• Design and launch enterprise-wide dashboards and data visualization tools to track key enterprise and business metrics, for internal clients, stakeholders, and the executive team
• Identify opportunities to streamline and automate reports, common business questions, etc.
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 3+ years in business intelligence, product analytics, data management, or data governance
• Proficiency in Python, SQL, and data APIs to work with large, complex datasets across multiple business domains
• Understand, and prototype scripts to support data pipelines, business rules, quality checks, and general data lifecycle activities
• Expert with DBT, Airflow, and other ETL/ELT orchestrators
• Expert with version control (Github, code review)
• Proficiency with GCP, AWS, or other big data environments
• Familiarity with business intelligence tools and developing dashboards
• Knowledge of industry-leading data governance, quality, and data management practices and tools

Preferred Qualifications:

• Expertise with JSON, YAML, relational data modeling, and other data modeling languages and tools
• Experience working with event-based and behavioral data and instrumentation

REQ-019606

About the Role

We are seeking a Principal Software Engineer to lead the architecture and evolution of our data and machine learning infrastructure. This role will shape the foundation on which data-driven products, analytics, and AI applications are built. You will design systems that enable large-scale data processing, reliable pipelines, and efficient machine learning development—from feature engineering to real-time model serving.

As a principal engineer, you will partner with product, data science, and platform teams to set technical direction, drive adoption of reusable frameworks, and mentor engineers across the organization. You will ensure that both data and ML platforms are scalable, reliable, cost-efficient, and compliant with privacy and governance standards.

The core of the Data Platform is a data lake on AWS S3 with Apache Iceberg as the table format to ensure reliability. Data ingestion is standardized through Confluent Kafka for real-time streaming and Fivetran for ingestion of files and change-data. The transformation layer is decoupled from storage, using Apache Flink for stream processing, AWS Glue (Spark) for core ETL , and dbt/Athena for building analytical data models. The platform serves data through fit-for-purpose data stores, including Amazon DynamoDB for low-latency applications and Google BigQuery as the primary engine for analytics and BI.

You will report to the Sr. Director of Engineering. This role can be remote in the US, with a preference for candidates in the New York City area.

Responsibilities:

• Architect & Build Platform: Design and evolve infrastructure for data ingestion, storage, batch and streaming pipelines, and machine learning workflows

• Enable ML at Scale: Build systems for training, deploying, monitoring, and governing models, including feature stores, registries, and inference platforms

• Reliability & Observability: Ensure end-to-end system reliability, monitoring, and cost transparency across data and ML workloads

• Self-Service Platforms: Deliver frameworks and APIs that enable engineers, analysts, and ML scientists to build and operate solutions independently

• Innovation & Standards: Evaluate and introduce emerging technologies (vector databases, distributed training, orchestration frameworks, LLM stacks) and establish adoption guidelines

• Cross-Functional Leadership: Partner with platform, product, and engineering and ML science leaders to align on strategy and accelerate delivery

• Mentorship & Influence: Guide senior and staff engineers, lead architecture reviews, and raise the technical bar across data and ML domains

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world
  
  

Basic Qualifications:

• 10+ years of software engineering experience with a focus on distributed systems, data platforms, and ML infrastructure or equivalent

• Proven ability to influence technical direction across multiple teams and mentor senior/staff engineers

• Proven expertise in data processing frameworks and table formats (e.g. Spark, Flink, Iceberg) and orchestration tools (e.g. Airflow, Kubeflow)

• Deep knowledge of ML infrastructure: model training pipelines, feature stores, registries, serving, and monitoring

• Strong programming skills in Python and at least one compiled language like Java or Go

• Experience designing systems with scalability, reliability, and cost-efficiency as first-class concerns

• Cloud platform experience (AWS, GCP), familiarity with Kubernetes and modern data platform architectures

• Familiarity with compliance and governance in data/ML systems (auditability, privacy, explainability)

• Familiarity with the data lakehouse paradigm and medallion architecture

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Remote

REQ-018968

About the Role:

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning & AI team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements guaranteed by our platform.

As an MLOps Engineer you will partner with product, data science and ML platform engineers to build and maintain the infrastructure that powers the machine learning lifecycle. You will automate and refine the training, deployment, monitoring, and management of our ML models.

This role reports to the Senior Engineering Manager of Data Management Infrastructure.

Responsibilities:

• Build and Automate ML Pipelines: by owning robust CI/CD pipelines for automated model training, validation, deployment, and retraining.

• Productionalize Models: Build the process for packaging, containerizing, and deploying ML models as scalable, low-latency, and highly-available services.

• Monitoring and Operations: Implement and manage comprehensive monitoring for production models, tracking system health, data drift, and model performance degradation.

• Tooling and Infrastructure: Manage and evolve our MLOps toolchain, including model registries, feature stores, experiment tracking systems, and model serving platforms.

• Collaboration and Support: Partner with data scientists to understand model requirements and optimize them for production. Support software engineers in integrating with ML services.

• Best Practices and Governance: Champion and enforce MLOps best practices for reproducibility, versioning (data, code, model), testing, and governance.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 2+ years of software engineering or DevOps experience with a focus on MLOps, automation, and infrastructure

• 2+ years of experience programming in Python or Go

• Experience building and managing CI/CD pipelines (e.g., Github Actions, Jenkins, GitLab CI)

• Hands-on experience with containerization and orchestration (e.g., Docker, Kubernetes)

• Cloud platform experience (AWS, GCP) and familiarity with infrastructure-as-code (e.g., Terraform, CloudFormation)

Preferred Qualifications:

• Experience with MLOps tools (e.g., MLflow, Kubeflow)

• Experience with the machine learning model lifecycle, from experimentation to production

• Experience with data processing frameworks (e.g., Spark, Dask, or Ray)

• Experience with low-latency no-sql datastores (BigTable, Dynamo, etc)

• Familiarity with monitoring and observability stacks (e.g., Prometheus, Grafana, Datadog, or ELK)

• Knowledge of data engineering pipelines and orchestration tools (e.g., Airflow, Prefect)

REQ-019522

#LI-hybrid

About the Role

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning Platform (MLP) team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models with low-latency and Service Level Agreements (SLAs) guaranteed by the MLP.

We are looking for a Software Engineer, with a focus on MLOps, to join our Machine Learning Platform team to help solve creative challenges around Machine Learning infrastructure for the New York Times.

This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.

Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform at scale

• You will build infrastructure to train and test algorithms that provide real-time content recommendations and personalization

• You will enhance ML platform's CI/CD and integration testing capabilities

• You will promote developer productivity by rolling out capabilities that maximize self-sufficiency and minimize the toil in learning those capabilities in building scalable applications with high speed, quality, and performance

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 2+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment

• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)

• Experience working with Kubernetes, Docker, and CI/CD

• Familiarity with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, Drone, Triton, TensorFlow, scikit-learn, DataDog

• Experience building real-world machine learning applications like recommendation systems, bandits, etc.

• Experience engaging with stakeholders to understand pain points, observe patterns, and identify opportunities for improvements

This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

REQ-019501

#LI-Hybrid

About the Role, Mission or Department Overview

The Data Platform Mission aims to empower the organization to access and use data to answer important questions, power user experiences, and to make strategic decisions that drive value and impact across the organization.

We are looking for Analytics Engineers that can help develop a new function within Data Platform that focuses on supporting our most critical data assets across The New York Times data domains. You will partner with many different teams and roles to develop data products, capabilities, and technologies. This role is based in our New York City office in Times Square.

As a Senior Analytics Engineer, you'll work with teams across the organization to manage, support, and improve the quality of data across specific organizational domains that help to make data-driven decisions and experiences as efficient as possible. You will develop deep expertise within specific data domains, being a subject matter expert for the business and being an important partner across data initiatives. You will report to the Executive Director of Analytics Engineering.

Responsibilities:

Data Platform Evangelist

• Provide frameworks, training, and guidance to individuals across the organization to utilize data platform capabilities or to submit well-defined data needs and requests
• Establish data management frameworks that provide clear recommendations and requirements for data producers, while also working with data platform team to integrate into capabilities
• Embed and work closely with data platform teams to build out governance into core capabilities

Data Quality

• Create and maintain data quality frameworks, definitions, and metrics that are consistently applied across data domains, products, and key data assets

• Define and test business logic to identify and surface domain-specific quality measures in conjunction with other data teams, that can be passed to data platform teams to implement once validated
• Establish a process to implement, track, and ensure data quality frameworks are adhered to
• Proactively monitor, surface, triage and track key data issues for data products and systems that provide visibility for data producers and data consumers to react accordingly, including the development of enterprise dashboards
• Partner with data engineering teams to test and build out capabilities that promote quality, including data lineage, testing frameworks, writing quality checks, etc.

Domain Support

• Maintain, update, and evolve our enterprise data and metrics catalogs
• Ensure the accuracy, completeness, consistency, and reliability of data within assigned domains
• Collaborate with various teams to understand domain needs, prioritize initiatives, maintain data models, and oversee the implementation of data governance standards
• Continuously improve data quality, identifies issues, and develops solutions to comply with regulatory requirements
• Document data management standards and supports business data stewards
• Identify and resolve data issues and risks within the domain
• Monitor domain maturity index with KPIs of data governance, quality, integration, security, and analytics
• Develop domain-specific documentation such as Data Use Cases and Data Flow Diagrams
• Provide support and training to the business regarding data governance and modeling

Analytics Enablement

• Work closely with data platform to pilot, test, and build out user-friendly ways to consume data products
• Collaborate with business stakeholders, Data and Insights teams, and Data Platform product managers to gather requirements and translate into effective, user-friendly dashboards, reports, datasets, or artifacts
• Design and launch enterprise-wide dashboards and data visualization tools to track key enterprise and business metrics, for internal clients, stakeholders, and the executive team
• Identify opportunities to streamline and automate reports, common business questions, etc.
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 5+ years in business intelligence, product analytics, data management, or data governance
• Proficiency in Python, SQL, and data APIs to work with large, complex datasets across multiple business domains
• Understand, and prototype scripts to support data pipelines, business rules, quality checks, and general data lifecycle activities
• Expert with DBT, Airflow, and other ETL/ELT orchestrators
• Expert with version control (Github, code review)
• Proficiency with GCP, AWS, or other big data environments
• Familiarity with business intelligence tools and developing dashboards
• Knowledge of industry-leading data governance, quality, and data management practices and tools

Preferred Qualifications:

• Expertise with JSON, YAML, relational data modeling, and other data modeling languages and tools
• Experience working with event-based and behavioral data and instrumentation

REQ-019608 

About the Role:

The position of the Data Engineer will be part of the Partner Revenue team that develops and deploys data platforms for advanced analytics and data processing. The Data Engineer defines and builds the data pipelines to promote faster, better, data-informed decision-making within the business.

The role is a hybrid position requiring 3 days a week in the office. You will report to the Director of Partner Revenue Technology.

Responsibilities:

• You will develop scalable data and ETL solutions
• You will develop scalable data platform components
• You will support existing platforms and implement data pipelines that ingest, transform, and curate data
• You will support any future migrations to new platforms using cloud-based technologies
• Demonstrate support and understanding of our value of journalistic independence and a commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 2+ years knowledge and experience in SQL for querying and data modeling
• 2+ years experience with any ETL frameworks or tools preferably Pentaho Data Integration or similar tools
• Demonstrated programming skills in Python and Shell scripting or similar language

Preferred Qualifications:

• Knowledge in data modeling and data warehouse concepts and have technical abilities to develop and debug complex code using AWS/GCP cloud infrastructure
• Experience with ETL Tools, Shell scripting, SQL, Python, Java, Airflow, dbt with the understanding of data flows, data warehouse architecture, ETL concepts and processing of structured and unstructured data
• Proven knowledge of CI/CD practices and version control (Git)
• Demonstrated ability to code with VSCode or similar IDE tools with the ability to use AI coding assistant tools such as cursor and github copilot

About the Role:

We are part of a New York-based technology organization with a remote-friendly workplace that includes engineers around the world. We value transparency and openness, learning, community, and continuous improvement. Check out the Times Open blog, which is written by engineers and other technical team members, and follow @nytdevs on Twitter to see what we're up to.

Responsibilities:

• Design, model, and implement complex ELT/ETL pipelines for the cleansed and curated data layers in the medallion architecture, taking full ownership of the data product's structure, partitioning, documentation, and performance characteristics.

• Develop advanced data transformations using dbt (data build tool) for relational data modeling and PySpark for large-scale data processing within the Lakehouse, ensuring outputs meet strict Service Level Agreements and quality standards.

• Collaborate across teams to define requirements and translate them into robust and scalable data models suitable for analytic consumption.

• Manage the physical data storage across both GCP and AWS, selecting optimal file formats and designing efficient partitioning and clustering strategies.

• Administer and tune Spark compute resources (e.g., Dataproc, EMR, or managed services) to optimize job execution time and cost.

• Own core components of our centralized analytics environment, specifically focused on Hex, integrations, and the methods of data exposure and access controls; and support data activation strategies, ensuring seamless data consumption by analytic tools.

• Optimize user queries and access patterns to maintain platform performance and cost efficiency.

• Implement centralized data quality checks and observability mechanisms within the data pipeline to proactively identify and resolve data issues.

• Contribute to the implementation of metadata management, data lineage, and role-based access control (RBAC) initiatives across the Lakehouse environment.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 2+ years of hands-on experience in a Data Engineering, Data Warehousing, Analytics Engineering or equivalent role

• Proficiency in SQL and experience with complex, production-level data modeling (dimensional modeling, Kimball, OBT, or Data Vault)

• Demonstrated experience designing, developing, and deploying end-to-end data products through the full Software Development Lifecycle

• Experience with a Cloud Data Warehouse, like BigQuery

• Proficiency in Python for scripting and data manipulation, including knowledge of PySpark or other Spark APIs

• Familiarity with cloud services and data storage components in at least one major cloud provider (GCP or AWS)

• Experience with workflow orchestration tools (e.g., Airflow, Cloud Composer, or Prefect) and version control systems (Git)

Preferred Qualifications:

• Experience operating in a dual-cloud environment (GCP/AWS)

• Experience with Infrastructure-as-Code (IaC) tools like Terraform

• Experience with advanced Lakehouse file formats like Iceberg or Delta Lake

• Familiarity with experimentation or A/B testing platforms and the data required to support them

• Experience in data product quality standards through integration advanced testing, quality checks, and monitoring into the CI/CD pipeline

REQ-019489

#LI-hybrid

About the Role

The New York Times is looking for a Senior Software Engineer, with a focus on ML platform development, to join our Machine Learning & AI team to help solve creative challenges around Machine Learning infrastructure.

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning & AI team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements (SLAs) guaranteed by our platform.

This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.

Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform that supports large-scale multi-tenant workloads

• You will build a platform to train and test algorithms that provide real-time content recommendations and personalization to our readers

• You will enhance ML platform's CI/CD and integration testing capabilities

• You will build a platform that supports the full Machine Learning workflow; from model training, testing and production deployment at high scale and low latency

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 5+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment

• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)

• Experience working with Kubernetes, Docker, and CI/CD (Drone, Argo, Jenkins, etc)

• Experience leading the development of large-scale, data-driven, distributed multi-tenant systems

• Proficiency with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, BigTable or other NoSQL datastores such as Cassandra, DynamoDB, Redis

• Familiarity with ML tooling such as Triton, TensorFlow, scikit-learn

• Experience building the infrastructure that power real-world machine learning applications like recommendation systems, bandits, etc.

• Experience engaging with partners to understand pain points, observe patterns, and identify opportunities for improvements

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

REQ-019502

#LI-hybrid

Octus is seeking a Principal Data Engineer to roll up their sleeves and build scalable, production-grade data pipelines and infrastructure. You'll be a hands-on technical leader — writing code daily, solving hard engineering problems, and helping elevate the team around you through doing. Spanning Snowflake, Databricks, and AWS, you'll be deeply involved in the day-to-day development of the data platform that powers Octus's products, data, and automation initiatives. The ideal candidate is an expert in Python and SQL who thrives in an execution-focused environment and has deep experience building modern data pipelines and lakehouse solutions.

Responsibilities

• Build and maintain end-to-end data pipelines — from raw ingestion through transformation and delivery — across diverse data sources (APIs, web data, internal feeds, etc.).
• Hands-on development of scalable, production-grade pipelines within Databricks, including Delta Lake table management, Workflows, and cluster optimization.
• Build and maintain data models, schemas, and transformation logic in Snowflake, optimizing for performance and reliability.
• Develop and manage Databricks environments including Unity Catalog, Delta Live Tables, and integration patterns that support both internal data consumers and external sharing use cases.
• Build and manage orchestration workflows using AWS services (MWAA/Airflow, Lambda, ECS, SQS, MSK) and Databricks-native orchestration where appropriate.
• Implement and maintain infrastructure as code (IaC) using Terraform, ensuring reproducibility and compliance with cloud standards.
• Establish and enforce best practices in data modeling, schema design, and ETL/ELT processes for high-volume structured and semi-structured data across Snowflake and Databricks.
• Ensure data quality, lineage, and observability through automated testing, monitoring, and alerting across all pipeline layers.
• Collaborate closely with technology leadership to align data platform development with business strategy and product goals.
• Stay at the forefront of industry trends in data engineering, lakehouse architecture, and cloud-native data platforms.

Requirements

• Strong foundation in software engineering principles, including SOLID design, modularity, and scalability.
• Expert proficiency in Databricks, including Delta Lake, Unity Catalog, Delta Live Tables, MLflow, and Databricks Workflows.
• Deep experience with Snowflake, including data modeling, performance optimization, and integration with upstream/downstream pipeline tooling.
• Expert proficiency in Python for data pipeline and automation development.
• Advanced SQL skills with experience optimizing complex queries and data models at scale.
• Proven experience designing and maintaining cloud-native data pipelines on AWS (e.g., MWAA/Airflow, Lambda, ECS, SQS, Glue, S3, Redshift, etc.).
• Experience implementing and managing Terraform or similar IaC frameworks.
• Strong understanding of lakehouse architecture patterns, data ingestion, transformation, and orchestration, including familiarity with ML/AI pipeline integration patterns.
• Familiarity with CI/CD pipelines, automated testing, and modern DevOps practices.
• 8+ years of experience in data engineering or backend development, with a focus on scalable data solutions.
• Demonstrated experience leading data infrastructure projects end-to-end and mentoring senior engineers.
• Familiarity with containerization (Docker) and workflow orchestration best practices.
• Excellent communication, collaboration, and problem-solving skills.

Nice to Have

• Experience with streaming data technologies (Kafka, Kinesis, Flink).
• Exposure to ML/AI pipeline patterns (feature stores, experiment tracking, model serving) and MLOps tooling, particularly in a cross-functional team environment.
• Experience integrating data quality and observability tools.
• Experience with Databricks as a data sharing and collaboration platform (Delta Sharing, Marketplace).
• Familiarity with Claude Code or similar AI-powered developer tools for accelerating pipeline development and code workflows.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $175,000 - $220,000

The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors.

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

While previous experience in the trading and finance industry is beneficial, we’re looking for talented software engineers with or without industry-specific expertise. We are open to remote workers for this role with the correct set of skils.

UP (Unified Platform) consolidates data and technologies into a comprehensive solution, accelerating time to market. Optimizing decision-making and research, our platform simplifies implementing new ideas, enhancing our competitive edge.

UP - PI (Platform Infrastructure) Writes and operates systems that accelerate other development teams. They provide managed services to technologists across all of DRW, helping domain experts focus on their business-critical goals. They create software to connect people, projects, and information, preventing silos and opacity.

For the appropriate candidate, we are open to remote employees for this role.

Expectations:

• Write, maintain, operate and improve managed infrastructure services for technologists firm-wide
• Design and communicate standards for how centrally managed services can be used
• Support internal technologists with triage, education, and consulting
• Write, maintain, operate, and improve bespoke applications for internal use, focused on visibility and integration across teams.
• Enable other teams to focus on business domains.
• Influence outcomes through dozens of software teams.
• Broadcast contagious passion for developer experience.
• Consolidate diverse and redundant approaches to common problems.

Desirable Experience:

• Three or more years of high impact contributions in Software Engineering, DevOps, SRE, Platform Engineering or adjacent roles
• Expertise in operating infrastructure at scale
• Expertise in Kubernetes, Apache Airflow, Kafka, Redis
• Proficiency in at least one of Python, Go, Java, Ruby
• Comfort deploying software to the cloud and on-premises
• Proven success in elevating standards for non-functional requirements like security, observability, reliability, and speed of delivery
• Informed perspective about AI Agents as development tools
• Record of accomplishment of enhancing the capabilities of other engineers and teams

The annual base salary range for this position is $100k to $175k depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

[#LI-SK1] 

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.

About the Role:

We are looking for a Senior Software Engineer to architect, build, and maintain the data infrastructure at Gusto.  As part of the Data Platform team, you will collaborate closely with Data Science, Business Intelligence, and analysts across Gusto teams to help them achieve their goals. 

The Data Platform position is a software development role with knowledge of data architectures and data delivery. The ideal candidate is passionate about developing software, working with data, and

Here’s what you’ll do day-to-day:

• Architect, build, and refine our infrastructure and tools that enable other teams to work with data.
• Efficiently handle vast amounts of clickstream, database, and third party application data, processing in batch and real-time
• Take full ownership of the solutions you build, working with stakeholders to develop requirements, implement solutions, monitor production, and troubleshoot problems that arise.
• Work as part of a team. We value team players who share their knowledge and like collaborating with others.

Here’s what we're looking for:

• • At least 7 years of software engineering experience.
  • Experience building solutions in the cloud, AWS preferred (Redshift, MSK, EMR).
  • Experience with OLAP databases (Clickhouse)
  • Experience building data pipelines at scale, Airflow and Python preferred.
  • Experience with streaming systems desired (Kafka, Kinesis, or similar).
  • Ability to turn vague requirements into clear deliverables with minimal guidance.
  • Experience building and maintaining a modern data stack in production.

Our cash compensation amount for this role is targeted at $163,000-$204,000/year in Denver, $178,000-$223,000/year in Los Angeles, and $197,000-$247,000/year for San Francisco, New York, and Seattle. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

About the role:

We are looking for a Staff Software Engineer to join our team and help us develop the core systems powering our clinical research. You will work closely with a talented product and data science team, stay up-to-date with the latest technologies, and contribute to a fast-paced, innovative environment. The ideal candidate for this role should be able to deliver across the tech stack and is eager to learn and apply new techniques and technologies.

Where you will work:

This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday.

What you will do:

• Design and build extensible systems that can grow with the business needs
• Collaborate across disciplines to understand our domain and iterate on new ideas
• Lead technical strategy and decision-making
• Protect our users’ privacy and security through secure coding practices

What you will bring to the team:

• 7+ years hands-on work delivering full-stack software
• Excellent communication skills and ability to clearly communicate design rationale and concepts
• Familiarity with Python, React, NodeJS, Docker, and AWS
• Excellent understanding of SQL and data modeling
• Familiarity building scalable data pipelines, query optimization, data modeling, and defining reusable datasets
• Experience working in a team using agile methodologies and fluency with the agile toolkit
• Experience mentoring team members and acting as a technical multiplier
• A willingness to “roll up your sleeves” and do whatever is necessary to ensure company success
• A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Claude Code, Kubernetes, AWS, Airflow, dlt, dbt, Python, TypeScript, React, Go

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Compensation Transparency:

The target salary range for this position is $240,000 - $285,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k), Teladoc Health and more.

About the role:

We are seeking an exceptional Software Engineer II to join our Engineering team. Garner’s Engineering team tackles incredibly hard technical problems for a mission that truly matters. Our systems analyze billions of medical records to rank healthcare providers across the country. We are an AWS + Kubernetes shop, and we are constantly introducing new technologies as our system load doubles every year. We expect our engineers to champion cutting-edge industry practices as we aggressively embrace AI in every facet of our operations and norms. We are seeking teammates who take pride in delivering their best work while fostering a strong team culture.

Where you will work:

This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. 

What you will do:

• Use AI to build, optimize, and maintain software systems
• Collaborate across disciplines to understand our domain and iterate on projects
• Protect our users’ privacy and security through best practices

The ideal candidate has:

• 2+ years of software engineering experience, especially with distributed event-driven architectures
• A generalist software engineering mindset ready to learn new languages, frameworks, and techniques required for a fast paced startup environment
• Familiarity with data security and HIPAA compliance
• A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Claude Code, Kubernetes, AWS, Airflow, dlt, dbt, Python, TypeScript, React, Go

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time.

Compensation Transparency:

The target salary range for this position is $150,000 - $170,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k), Teladoc Health and more.

About the role:

We are seeking an exceptional Senior Software Engineer to join our Engineering team. Garner’s Engineering team tackles incredibly hard technical problems for a mission that truly matters. Our systems analyze billions of medical records to rank healthcare providers across the country. We are an AWS + Kubernetes shop, and we are constantly introducing new technologies as our system load doubles every year. We expect our engineers to champion cutting-edge industry practices as we aggressively embrace AI in every facet of our operations and norms. We are seeking teammates who take pride in delivering their best work while fostering a strong team culture.

Where you will work:

This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. 

What you will do:

• Lead technical strategy and decision-making on assigned domains
• Use AI to build, optimize, and maintain software systems
• Mentor and uplevel early-career engineers
• Collaborate across disciplines to understand our domain and iterate on projects
• Protect our users’ privacy and security through best practices

The ideal candidate has:

• 4+ years of software engineering experience
• A generalist software engineering mindset ready to learn new languages, frameworks, and techniques required for a fast paced startup environment
• Demonstrated ability to build complex systems using AI coding agents (we use Claude Code)
• The ability to learn quickly and mentor others
• Familiarity with data security and HIPAA compliance
• A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Claude Code, Kubernetes, AWS, Airflow, dlt, dbt, Python, TypeScript, React, Go

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Compensation Transparency:

The target salary range for this position is $190,000 - $240,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k), Teladoc Health and more.

About the role:

We are seeking an exceptional Senior Data Engineer with a high sense of ownership who is excited about our mission, eager to learn and teach others, and can deliver across the tech stack. This role will report to our VP, Engineering. The ideal candidate should have experience with a modern data stack and implementations of data pipelines using Python and SQL in AWS. 

Where you will work:

This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. 

What you will do:

• Build, optimize, and maintain data pipelines that power our business
• Define and build out abstracted reusable data sets to be used for Business Intelligence, Marketing, and Data Science Research
• Design, build, and evangelize a federated data validation frameworks to be used to monitor potential data inconsistencies
• Protect our users’ privacy and security through best practices

The ideal candidate has:

• 4+ years of software/data engineering experience (distributed data processing, data warehousing, data governance, Big Data, data variance, data privacy, and data quality)
• Expertise in SQL, job experience, and demonstrated strength with Python
• Expertise in building scalable data pipelines, query optimization, data modeling, and defining reusable datasets
• Experience working with orchestration tools (especially Airflow), databases (especially PostgreSQL), datalakes (especially Iceberg), data warehouses (especially Snowflake)
• Expertise with SQL tuning, Spark development, medallion and event-driven architectures. 
• Familiarity with healthcare or insurance
• Familiarity with data security and HIPAA compliance
• A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Postgres/SQL, Snowflake, Python, AWS, Terraform, Argo, Airflow, Spark, DuckDB, Iceberg, Airbyte, DBT, ElasticSearch (aka OpenSearch), OpenTelemetry, Looker

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Compensation Transparency:

The target salary range for this position is $180,000.00 - $220,000.00. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more.

About the role:

We are seeking an exceptional Director, Engineering to join our Search team. This role will report to the Chief Technology Officer. The Search team owns our provider recommendations system, provider data aggregation pipelines, and our AI-powered member support systems.

Where you will work:

This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. Relocation assistance is available for non-local candidates.

What you will do:

• Lead the development of a world-class Search system that organizes provider data in order to deliver relevant and impactful recommendations to our members
• Own and drive the execution of relevant quarterly deliverables and long-term strategy
• Collaborate closely with cross-functional teams to align strategies and achieve company objectives
• Provide leadership and guidance to your teams, fostering a culture of excellence, collaboration, and accountability
• Ensure your team proactively incorporates relevant new technologies, system designs, and strategies, especially in the domains of big data, ML, and AI
• Influence relevant partner teams in order to accelerate delivery across the organization
• Champion and ensure the privacy and security of our users’ data
• Mentor, grow, and recruit Garner’s next generation of engineering leaders

The ideal candidate has:

• 6+ years in software engineering, including 3+ years managing software or data engineering teams
• 1+ year managing engineering managers
• Experience operating production ML systems for user-facing use cases using modern ML platforms (e.g., SageMaker, Vertex AI, MLflow, BentoML, or similar)
• Familiarity with feature engineering technologies, including DataFrame-based processing frameworks and feature stores used in production systems
• Familiarity with the production ML lifecycle, including how models are packaged, deployed, and iterated over time; model development experience is not required
• Familiarity with data engineering concepts that support ML-powered systems, including large-scale data processing and orchestration (e.g., Spark, Airflow, or similar) used to produce and maintain model features
• Experience with personalization, recommendation, or search systems preferred
• Ability to translate complex business needs into a clear, executable technical roadmap
• Experience working with regulated data; healthcare data standards (HIPAA, EDI) a plus
• A willingness to “roll up your sleeves” and do whatever is necessary to ensure company success
• Experience working in a rapidly evolving startup environment 
• A desire to be a part of our mission to improve the U.S. healthcare system
• A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Python, TypeScript, React, Kubernetes, Postgres, AWS, NATS, Airflow, Snowflake

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Compensation Transparency:

The target salary range for this position is $285,000 - $315,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k), Teladoc Health and more.

About the role:

We are seeking an exceptional Data Engineer II to join our Engineering team, with a high sense of ownership who is excited about our mission, eager to learn and teach others, and can deliver across the tech stack. The ideal candidate should have experience with a modern data stack and implementations of data pipelines using Python and SQL in AWS. 

Where you will work:

This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday.

What you will do:

• Build, optimize, and maintain data pipelines that power our business
• Define and build out abstracted reusable data sets to be used for Business Intelligence, Marketing, and Data Science Research
• Design, build, and evangelize a federated data validation framework to be used to monitor potential data inconsistencies
• Protect our users’ privacy and security through best practices

The ideal candidate has:

• 2+ years of software/data engineering experience (distributed data processing, data warehousing, data governance, Big Data, data variance, data privacy, and data quality).
• Expertise in SQL and Python
• Expertise in building scalable data pipelines, query optimization, data modeling, and defining reusable datasets
• Experience working with orchestration tools (especially Airflow), databases (especially PostgreSQL), data warehouses (especially Snowflake)
• Familiarity with SQL tuning, medallion/event-driven architectures, and telemetry.
• Familiarity with healthcare or insurance
• Familiarity with data security and HIPPA compliance
• A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use:

Postgres/SQL, Snowflake, Python, AWS, Terraform, Argo, Airflow, Spark, DuckDB, Iceberg, Airbyte, DBT, ElasticSearch (aka OpenSearch), OpenTelemetry, Looker

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time.

Compensation Transparency:

The target salary range for this position is $125,000-$165,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more.

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 38 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences.

We’re looking for a Data Engineer II to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Data Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform- one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. 

A brief highlight of our tech stack:

• SQL / Python / Looker / Snowflake / dbt

What you'll do:

• Build a scalable data system in which Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner 
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• Develop and maintain data pipelines to collect, clean, and transform data (owning end to end data product from ingestion to visualization)
• Develop and implement data analytics models
• Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems
• Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR

What you're great at:

• 4+ years of data engineering experience
• Working with cloud-based application development, and be fluent in at least a few of: 
• Cloud services providers like AWS
• Data pipeline orchestration tools like Airflow, Dagster, Luigi, etc
• Big data tools like Spark, Kafka, Snowflake, Databricks, etc
• Collaboration, integration, and deployment tools like Github, Argo, and Jenkins 
• Data visualization tool like Looker, Tableau, etc
• Articulating technical concepts to a mixed audience of technical and non-technical stakeholders
• Collaborating and mentoring less experienced members of the team
• Comfort with ambiguity 
• Curiosity about technology, believe in constant learning, and ability to be autonomous to figure out what's important

How You’ll be Rewarded:

At CLEAR, we help YOU move forward - because when you’re at your best, we’re at our best. You’ll work with talented team members motivated by our mission of making experiences safer and easier. Our offices are bright and energetic with an open concept and plenty of conference rooms and casual co-working spaces. We also offer catered lunches every day and have fully stocked kitchens. Outside of the office, we invest in your well-being and learning & development with stipends and reimbursement programs. 

We offer holistic total rewards, including comprehensive healthcare plans, family-building benefits (fertility and adoption/surrogacy support), flexible time off, annual wellness stipend, free OneMedical memberships for you and your dependents, a CLEAR Plus membership, and a 401(k) retirement plan with employer match. The total compensation range for this role is $180,000-$220,000, depending on levels of skills and experience.

This range represents the combined base salary and new hire equity package (in Restricted Stock Units) for this position at CLEAR. Additionally, this role will be eligible for refresh equity grants as part of our ongoing compensation program. Actual compensation will vary based on factors including, but not limited to, location, education, skills, experience, and performance. All stock based compensation will be subject to the terms and conditions of applicable agreements.

CLEAR provides reasonable accommodation to qualified individuals with disabilities or protected needs. Please let us know if you require a reasonable accommodation to apply for a job or perform your job. Examples of reasonable accommodation include, but are not limited to, time off, extra breaks, making a change to the application process or work procedures, policy exceptions, providing documents in an alternative format, live captioning or using a sign language interpreter, or using specialized equipment.

We are committed to a transparent and secure hiring process. All communications related to this role will come directly from a CLEAR employee through valid CLEAR channels (e.g., a valid @clearme.com email address or verified CLEAR LinkedIn profile). We encourage candidates to remain alert to job scams and to report any suspicious activity.

#LI-Onsite

About the Company

Gemini is a global crypto and Web3 platform founded by Cameron and Tyler Winklevoss in 2014, offering a wide range of simple, reliable, and secure crypto products and services to individuals and institutions in over 70 countries. Our mission is to unlock the next era of financial, creative, and personal freedom by providing trusted access to the decentralized future. We envision a world where crypto reshapes the global financial system, internet, and money to create greater choice, independence, and opportunity for all — bridging traditional finance with the emerging cryptoeconomy in a way that is more open, fair, and secure. As a publicly traded company, Gemini is poised to accelerate this vision with greater scale, reach, and impact.

The Department: Data

At Gemini, our Data Team is the engine that powers insight, innovation, and trust across the company. We bring together world-class data engineers, platform engineers, machine learning engineers, analytics engineers, and data scientists — all working in harmony to transform raw information into secure, reliable, and actionable intelligence. From building scalable pipelines and platforms, to enabling cutting-edge machine learning, to ensuring governance and cost efficiency, we deliver the foundation for smarter decisions and breakthrough products. We thrive at the intersection of crypto, technology, and finance, and we’re united by a shared mission: to unlock the full potential of Gemini’s data to drive growth, efficiency, and customer impact.

The Role: Staff Data Engineer

The Data team is responsible for designing and operating the data infrastructure that powers insight, reporting, analytics, and machine learning across the business. As a Staff Data Engineer, you will lead architectural initiatives, mentor others, and build high-scale systems that impact the entire organization. You will partner closely with product, analytics, ML, finance, operations, and engineering teams to move, transform, and model data reliably, with observability, resilience, and agility.

This role is required to be in person twice a week at our New York City, NY office.

Responsibilities:

• Lead the architecture, design, and implementation of data infrastructure and pipelines, spanning both batch and real-time / streaming workloads
• Build and maintain scalable, efficient, and reliable ETL/ELT pipelines using languages and frameworks such as Python, SQL, Spark, Flink, Beam, or equivalents
• Work on real-time or near-real-time data solutions (e.g. CDC, streaming, micro-batch) for use cases that require timely data
• Partner with data scientists, ML engineers, analysts, and product teams to understand data requirements, define SLAs, and deliver coherent data products that others can self-serve
• Establish data quality, validation, observability, and monitoring frameworks (data auditing, alerting, anomaly detection, data lineage)
• Investigate and resolve complex production issues: root cause analysis, performance bottlenecks, data integrity, fault tolerance
• Mentor and guide more junior and mid-level data engineers: lead code reviews, design reviews, and best-practice evangelism
• Stay up to date on new tools, technologies, and patterns in the data and cloud space, bringing proposals and proof-of-concepts when appropriate
• Document data flows, data dictionaries, architecture patterns, and operational runbooks

Minimum Qualifications:

• 8+ years of experience in data engineering (or similar) roles
• Strong experience in ETL/ELT pipeline design, implementation, and optimization
• Deep expertise in Python and SQL writing production-quality, maintainable, testable code
• Experience with large-scale data warehouses (e.g. Databricks, BigQuery, Snowflake)
• Solid grounding in software engineering fundamentals, data structures, and systems thinking
• Hands-on experience in data modeling (dimensional modeling, normalization, schema design)
• Experience building systems with real-time or streaming data (e.g. Kafka, Kinesis, Flink, Spark Streaming), and familiarity with CDC frameworks
• Experience with orchestration / workflow frameworks (e.g. Airflow)
• Familiarity with data governance, lineage, metadata, cataloging, and data quality practices
• Strong cross-functional communication skills; ability to translate between technical and non-technical stakeholders
• Proven experience in mentoring, leading design discussions, and influencing data-engineering best practices across teams

Preferred Qualifications:

• Experience with crypto, financial services, trading, markets, or exchange systems
• Experience with blockchain, crypto, Web3 data — e.g. blocks, transactions, contract calls, token transfers, UTXO/account models, on-chain indexing, chain APIs, etc.
• Experience with infrastructure as code, containerization, and CI/CD pipelines
• Hands-on experience managing and optimizing Databricks on AWS

• Competitive starting pay
• A discretionary annual bonus
• Long-term incentive in the form of a new hire equity grant
• Comprehensive health plans
• 401K with company matching
• Paid Parental Leave
• Flexible time off

Salary Range: The base salary range for this role is between $168,000 - $240,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.

In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in-person collaboration with the flexibility of remote work. Expectations may vary by location and role, so candidates are encouraged to connect with their recruiter to learn more about the specific policy for the role. Employees who do not live near one of our hubs are part of our remote workforce.

At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People Team know.

#LI-AA1

About the Company

Gemini is a global crypto and Web3 platform founded by Cameron and Tyler Winklevoss in 2014, offering a wide range of simple, reliable, and secure crypto products and services to individuals and institutions in over 70 countries. Our mission is to unlock the next era of financial, creative, and personal freedom by providing trusted access to the decentralized future. We envision a world where crypto reshapes the global financial system, internet, and money to create greater choice, independence, and opportunity for all — bridging traditional finance with the emerging cryptoeconomy in a way that is more open, fair, and secure. As a publicly traded company, Gemini is poised to accelerate this vision with greater scale, reach, and impact.

The Department: Customer Support (Ledger Operations)

As a team within the Support group, the team is data driven and customer-centric. Team members work closely with data scientists, engineers, product managers, and corporate operational stakeholders to reconcile data. Projects range from the very urgent, short sprint to redesigning long-term solutions to improve scalability and automation. Ledger Operations primary goal is to ensure high quality, scalable data reconciliation with proactive monitoring and reducing delays for reactive corrections. This team is responsible for building the “next generation” of reconciliation tools to maintain and expand Gemini’s internal reconciliation processes. 

The Role: Senior Ledger Operations Engineer

This role is required to be in person twice a week at our New York City, NY office.

Responsibilities:

• Build and maintain API adapters for Gemini trade data
• Design and optimize data pipelines for ledger operations
• Automate ETL (Extract, Transform, Load) processes
• Optimize SQL queries and database performance
• Contribute to the next generation of ledger reconciliation processes and reporting
• Collaborate with third-party vendors, Data Analytics team, and Cryptocore engineers
• Support data processing for the blockchain reconciliation project
• Develop and maintain data adapters for real-time data processing
• Create and implement data validation processes
• Develop customized reporting solutions
• Investigate and identify root causes of exception reports

Minimum Qualifications:

• 5+years implementing a reconciliation system while improving existing data pipelines
• Experience building real-time data solutions, data-lake and data warehousing technologies
• Experience building and integrating web analytics solutions
• Advanced SQL skills is a must
• Experience with gRPC, Websocket and REST API 
• Experience and expertise in Databricks, Spark/PySpark, Kafka streaming, Apache Flink, Airflow, Hadoop etc.
• Skilled in programming languages Python, Scala, Rust or Go
• Experience with one or more MPP databases(Redshift, Timescale,  StarRock)
• Able to identify gaps in existing reconciliation processes
• Extensive ETL and database experience with financial transaction systems for (banking systems, exchange systems)
• Experience with Datadog, cloudwatch or other alert monitoring systems

Preferred Qualifications:

• Financial certifications are not required, but encouraged. Understanding the regulatory landscape in traditional financial markets will lend well as the digital asset space evolves
• Financial Reporting Requirements for publicly traded companies

• Competitive starting pay
• A discretionary annual bonus
• Long-term incentive in the form of a new hire equity grant
• Comprehensive health plans
• 401K with company matching
• Paid Parental Leave
• Flexible time off

Salary Range: The base salary range for this role is between $126,000 - $180,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.

In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in-person collaboration with the flexibility of remote work. Expectations may vary by location and role, so candidates are encouraged to connect with their recruiter to learn more about the specific policy for the role. Employees who do not live near one of our hubs are part of our remote workforce.

At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People Team know.

#LI-AA1

About the Company

Gemini is a global crypto and Web3 platform founded by Cameron and Tyler Winklevoss in 2014, offering a wide range of simple, reliable, and secure crypto products and services to individuals and institutions in over 70 countries. Our mission is to unlock the next era of financial, creative, and personal freedom by providing trusted access to the decentralized future. We envision a world where crypto reshapes the global financial system, internet, and money to create greater choice, independence, and opportunity for all — bridging traditional finance with the emerging cryptoeconomy in a way that is more open, fair, and secure. As a publicly traded company, Gemini is poised to accelerate this vision with greater scale, reach, and impact.

The Department: Data

At Gemini, our Data Team is the engine that powers insight, innovation, and trust across the company. We bring together world-class data engineers, platform engineers, machine learning engineers, analytics engineers, and data scientists — all working in harmony to transform raw information into secure, reliable, and actionable intelligence. From building scalable pipelines and platforms, to enabling cutting-edge machine learning, to ensuring governance and cost efficiency, we deliver the foundation for smarter decisions and breakthrough products. We thrive at the intersection of crypto, technology, and finance, and we’re united by a shared mission: to unlock the full potential of Gemini’s data to drive growth, efficiency, and customer impact.

The Role: Principal Data Engineer

The Data Engineering Team owns the ingestion and transformation of data from production databases, streams, and external data sources into our data warehouse. As a Principal Data Engineer, you will set the technical direction for how data is modeled, processed, and delivered across the organization. You will partner closely with product, analytics, ML, finance, operations, and engineering teams to move, transform, and model data reliably, with observability, resilience, and agility. You’ll lead by example through design excellence, mentoring, and technical leadership, ensuring our data architecture is scalable, governed, and ready for the next generation of analytics and machine learning at Gemini. 

This is a senior individual contributor role — highly technical, strategic, and cross-functional — where you’ll influence the design of data systems that underpin key decisions and customer-facing products across Gemini.

This role is required to be in person twice a week at our New York City, NY office.

Responsibilities:

• Define and drive the long-term vision for data architecture, modeling, and transformation at Gemini
• Establish standards for data reliability, observability, and quality across all pipelines and data products using languages and frameworks such as Python, SQL, Spark, Flink, Beam, or equivalents
• Partner with Staff and Senior Data Engineers, Platform Engineers, and Analytics Engineers to unify how data is produced, stored, and consumed
• Lead large-scale design initiatives that span multiple teams and systems, ensuring maintainability, performance, and security
• Partner with data scientists, ML engineers, analysts, and product teams to understand data requirements, define SLAs, and deliver coherent data products that others can self-serve
• Establish data quality, validation, observability, and monitoring frameworks (data auditing, alerting, anomaly detection, data lineage)
• Investigate and resolve complex production issues: root cause analysis, performance bottlenecks, data integrity, fault tolerance
• Mentor and guide more junior and mid-level data engineers: lead code reviews, design reviews, and best-practice evangelism
• Help recruit and onboard new talent, shaping the future of Gemini’s data engineering discipline
• Stay up to date on new tools, technologies, and patterns in the data and cloud space, bringing proposals and proof-of-concepts when appropriate
• Document data flows, data dictionaries, architecture patterns, and operational runbooks

Minimum Qualifications:

• 10+ years of experience in data engineering (or similar) roles
• Strong experience in ETL/ELT pipeline design, implementation, and optimization
• Deep expertise in Python and SQL writing production-quality, maintainable, testable code
• Experience with large-scale data warehouses (e.g. Databricks, BigQuery, Snowflake)
• Solid grounding in software engineering fundamentals, data structures, and systems thinking
• Hands-on experience in data modeling (dimensional modeling, normalization, schema design)
• Experience building systems with real-time or streaming data (e.g. Kafka, Kinesis, Flink, Spark Streaming), and familiarity with CDC frameworks
• Experience with orchestration / workflow frameworks (e.g. Airflow)
• Familiarity with data governance, lineage, metadata, cataloging, and data quality practices
• Strong cross-functional communication skills; ability to translate between technical and non-technical stakeholders
• Proven experience in recruiting, mentoring, leading design discussions, and influencing data-engineering best practices across teams

Preferred Qualifications:

• Experience with crypto, financial services, trading, markets, or exchange systems
• Experience with blockchain, crypto, Web3 data — e.g. blocks, transactions, contract calls, token transfers, UTXO/account models, on-chain indexing, chain APIs, etc.
• Experience with infrastructure as code, containerization, and CI/CD pipelines
• Hands-on experience managing and optimizing Databricks on AWS

• Competitive starting salary
• A discretionary annual bonus
• Long-term incentive in the form of a new hire equity grant
• Comprehensive health plans
• 401K with company matching
• Paid Parental Leave
• Flexible time off

Salary Range: The base salary range for this role is between $192,500 - $275,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.

In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in-person collaboration with the flexibility of remote work. Expectations may vary by location and role, so candidates are encouraged to connect with their recruiter to learn more about the specific policy for the role. Employees who do not live near one of our hubs are part of our remote workforce.

At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People Team know.

#LI-AA1

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.

About the Role

As the Director, Data & Analytics Engineering, you will lead a team of Data and Analytics Engineers building the data foundation of the Charlie Health Operating Model, an AI-first model where the warehouse is no longer a passive reporting layer, but the substrate of our World  Model: a continuously updated, causal representation of every patient, provider, payor, and operational signal in our ecosystem.

You will own the pipelines, schemas, and storage systems that fuel both human and machine consumers, powering our 1,600+ dbt models, our real-time Intelligence Layer, and the agentic systems composing interventions on top of it. You will push us beyond Snowflake batch cycles into event-driven signal graphs that detect drift the moment a cohort's trajectory diverges from baseline, and you will architect the semantic retrieval surfaces that make our long-form clinical and operational artifacts AI-ready.

This is a hands-on, Player-Coach leadership role. You will set the technical vision, run sprint ceremonies and roadmap planning, mentor ICs and a Data Engineering Manager, support DRIs running cross-cutting 90-day missions, and stay close enough to the code to make sharp architectural calls and unblock the team. You will partner with leaders across ML, Data Science, BizOps, Product, and Engineering and own the shape of the data model architecture that the next decade of Charlie Health is built on.

We're a team of passionate, forward-thinking professionals eager to take on the behavioral health crisis and play a formative role in providing life-saving solutions. If you're inspired by our mission and energized by the idea that the distance between identifying an operational friction and shipping a clinical intervention should be measured in days rather than months, apply today.

Responsibilities

• Own the warehouse and pipeline architecture that powers the Charlie Health World Model, the causal, continuously updated representation of our ecosystem that fuels reporting, product analytics, and the agentic Intelligence Layer
• Drive the long-term roadmap for AI-ready data: real-time signal graphs beyond batch cycles, schema-validated event flows, and semantic retrieval surfaces for transcripts, notes, and other long-form artifacts
• Define and execute a vision for scalable data model architecture in Snowflake, evolving 1,600+ existing dbt models toward extensible, well-governed, agent-consumable patterns
• Partner with Machine Learning, Data Science, Engineering, Product, and BizOps to align data initiatives with company priorities and unlock new opportunities, particularly the agentic capabilities riding on top of the World Model
• Lead execution end-to-end: sprint ceremonies, roadmap planning, and prioritization, with the discipline to keep a growing team shipping high-quality, reliable solutions on schedule
• Oversee data integrity, documentation, testing, monitoring, and provenance across systems so that stakeholders, human and agent, can trust and self-serve on our data
• Guide and contribute to architecture and design decisions across our stack (Dagster, Snowflake, dbt, Fivetran, Hightouch, Hex, Tableau), and resolve critical technical issues as a hands-on technical leader
• Own the data infrastructure that powers company-wide KPI reporting, ad hoc analysis, product analytics, and dashboard development, ensuring the underlying models, pipelines, and semantic layer enable downstream teams to deliver clear, accurate insights as business questions evolve
• Drive reliability, scalability, observability, security, and cost-efficiency improvements across the data stack, including the PHI gatekeeping and HITRUST-aligned patterns that govern signal ingestion
• Identify bottlenecks and implement improvements to team workflows, tools, and development practices
• Manage and mentor a growing team of Data and Analytics Engineers and one Data Engineering Manager. Operate as a Player-Coach: focus on craft, mentorship, high-leverage code review, and supporting DRIs running 90-day cross-cutting missions
• Establish metrics that track progress, communicate priorities, and demonstrate business impact
• Define and maintain data governance standards and proactively manage stakeholder expectations to drive scalable, trusted data use

Requirements

• 10+ years of data or analytics engineering experience, with 4+ years managing and mentoring data and analytics engineers, with a focus on execution and delivery
• Proven ability to drive team operations, including sprint ceremonies, roadmap planning, and prioritization across multiple workstreams
• Hands-on background building and maintaining ELT pipelines using SQL, dbt, and OLAP databases like Snowflake
• Proficiency in Python (preferred) or another language strong enough to guide and review technical work
• Experience with workflow orchestration tools like Dagster, Airflow, or Prefect
• Skilled at building scalable reporting solutions in Tableau or Hex and enabling self-serve analytics across the organization
• Strong data modeling, provenance, and governance skills to support extensible, trusted, and consistent reporting and patterns
• Track record of improving team processes, optimizing workflows, and delivering measurable impact
• Effective cross-functional partner with Machine Learning, Data Science, Product and Engineering, aligning data work with business goals
• Clear, concise communicator who can translate complex technical concepts for non-technical stakeholders
• Comfortable navigating ambiguity, breaking down complex problems, and driving iterative solutions
• Committed people leader with a history of coaching talent and fostering a high-performance, inclusive team culture
• This role requires 4 days per week in our NYC office (Flatiron District)

Nice to Haves

• Familiarity with healthcare data standards (HIPAA, FHIR, HITRUST)
• Experience with AWS cloud technologies
• Experience working in a startup environment
• Exposure to event-driven architectures (EventBridge, Kafka, CloudEvents) and JSON Schema registries
• Familiarity with vector stores (Pgvector, Pinecone) and patterns for semantic retrieval over operational data
• Experience supporting ML or agentic AI workloads as a data consumer — designing schemas, features, or context surfaces that downstream models and agents rely on
• Awareness of LLMOps tooling and what it takes to keep AI systems observable and PHI-safe

Benefits

Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here.

Additional Information

The total target base compensation for this role will be between $250,000 and $325,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits.  #LI-HYBRID

About the Role

As the Director, Data & Analytics Engineering, you will lead a team of Data and Analytics Engineers building the data foundation of the Charlie Health Operating Model, an AI-first model where the warehouse is no longer a passive reporting layer, but the substrate of our World  Model: a continuously updated, causal representation of every patient, provider, payor, and operational signal in our ecosystem.

You will own the pipelines, schemas, and storage systems that fuel both human and machine consumers, powering our 1,600+ dbt models, our real-time Intelligence Layer, and the agentic systems composing interventions on top of it. You will push us beyond Snowflake batch cycles into event-driven signal graphs that detect drift the moment a cohort's trajectory diverges from baseline, and you will architect the semantic retrieval surfaces that make our long-form clinical and operational artifacts AI-ready.

This is a hands-on, Player-Coach leadership role. You will set the technical vision, run sprint ceremonies and roadmap planning, mentor ICs and a Data Engineering Manager, support DRIs running cross-cutting 90-day missions, and stay close enough to the code to make sharp architectural calls and unblock the team. You will partner with leaders across ML, Data Science, BizOps, Product, and Engineering and own the shape of the data model architecture that the next decade of Charlie Health is built on.

We're a team of passionate, forward-thinking professionals eager to take on the behavioral health crisis and play a formative role in providing life-saving solutions. If you're inspired by our mission and energized by the idea that the distance between identifying an operational friction and shipping a clinical intervention should be measured in days rather than months, apply today.

Responsibilities

• Own the warehouse and pipeline architecture that powers the Charlie Health World Model, the causal, continuously updated representation of our ecosystem that fuels reporting, product analytics, and the agentic Intelligence Layer
• Drive the long-term roadmap for AI-ready data: real-time signal graphs beyond batch cycles, schema-validated event flows, and semantic retrieval surfaces for transcripts, notes, and other long-form artifacts
• Define and execute a vision for scalable data model architecture in Snowflake, evolving 1,600+ existing dbt models toward extensible, well-governed, agent-consumable patterns
• Partner with Machine Learning, Data Science, Engineering, Product, and BizOps to align data initiatives with company priorities and unlock new opportunities, particularly the agentic capabilities riding on top of the World Model
• Lead execution end-to-end: sprint ceremonies, roadmap planning, and prioritization, with the discipline to keep a growing team shipping high-quality, reliable solutions on schedule
• Oversee data integrity, documentation, testing, monitoring, and provenance across systems so that stakeholders, human and agent, can trust and self-serve on our data
• Guide and contribute to architecture and design decisions across our stack (Dagster, Snowflake, dbt, Fivetran, Hightouch, Hex, Tableau), and resolve critical technical issues as a hands-on technical leader
• Own the data infrastructure that powers company-wide KPI reporting, ad hoc analysis, product analytics, and dashboard development, ensuring the underlying models, pipelines, and semantic layer enable downstream teams to deliver clear, accurate insights as business questions evolve
• Drive reliability, scalability, observability, security, and cost-efficiency improvements across the data stack, including the PHI gatekeeping and HITRUST-aligned patterns that govern signal ingestion
• Identify bottlenecks and implement improvements to team workflows, tools, and development practices
• Manage and mentor a growing team of Data and Analytics Engineers and one Data Engineering Manager. Operate as a Player-Coach: focus on craft, mentorship, high-leverage code review, and supporting DRIs running 90-day cross-cutting missions
• Establish metrics that track progress, communicate priorities, and demonstrate business impact
• Define and maintain data governance standards and proactively manage stakeholder expectations to drive scalable, trusted data use

Requirements

• 10+ years of data or analytics engineering experience, with 4+ years managing and mentoring data and analytics engineers, with a focus on execution and delivery
• Proven ability to drive team operations, including sprint ceremonies, roadmap planning, and prioritization across multiple workstreams
• Hands-on background building and maintaining ELT pipelines using SQL, dbt, and OLAP databases like Snowflake
• Proficiency in Python (preferred) or another language strong enough to guide and review technical work
• Experience with workflow orchestration tools like Dagster, Airflow, or Prefect
• Skilled at building scalable reporting solutions in Tableau or Hex and enabling self-serve analytics across the organization
• Strong data modeling, provenance, and governance skills to support extensible, trusted, and consistent reporting and patterns
• Track record of improving team processes, optimizing workflows, and delivering measurable impact
• Effective cross-functional partner with Machine Learning, Data Science, Product and Engineering, aligning data work with business goals
• Clear, concise communicator who can translate complex technical concepts for non-technical stakeholders
• Comfortable navigating ambiguity, breaking down complex problems, and driving iterative solutions
• Committed people leader with a history of coaching talent and fostering a high-performance, inclusive team culture
• This role requires 4 days per week in our NYC office (Flatiron District)

Nice to Haves

• Familiarity with healthcare data standards (HIPAA, FHIR, HITRUST)
• Experience with AWS cloud technologies
• Experience working in a startup environment
• Exposure to event-driven architectures (EventBridge, Kafka, CloudEvents) and JSON Schema registries
• Familiarity with vector stores (Pgvector, Pinecone) and patterns for semantic retrieval over operational data
• Experience supporting ML or agentic AI workloads as a data consumer — designing schemas, features, or context surfaces that downstream models and agents rely on
• Awareness of LLMOps tooling and what it takes to keep AI systems observable and PHI-safe

Benefits

Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here.

Additional Information

The total target base compensation for this role will be between $250,000 and $325,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits.  #LI-HYBRID

What You’ll Do:

The Platform & Infrastructure Engineering team in the Data Infrastructure organization is responsible for the reliability, scalability, and security of the company’s data platform. The team builds and operates the foundational systems that power data ingestion, transformation, analytics, and internal AI workloads at scale. We operate with production-grade discipline, supporting mission-critical services with stringent uptime requirements and a focus on automation, observability, and resilience.

About the role:

As a Senior Site Reliability Engineer, you will own the reliability and performance of our Kubernetes-based data platform. You will design and operate highly available, multi-region systems, ensuring our services meet strict uptime and latency targets. Day-to-day, you’ll work on scaling infrastructure, improving deployment pipelines, and hardening our security posture. You’ll play a key role in evolving our DevSecOps practices while partnering closely with engineering teams to ensure services are built for reliability from day one.

Who You Are: 

• 5+ years of experience in Site Reliability Engineering, Platform Engineering, or Infrastructure Engineering roles
• Deep expertise in Kubernetes and containerized software services, including cluster design, operations, and troubleshooting in production environments
• Strong experience building and operating CI/CD systems, including tools such as Argo CD and GitHub Actions
• Proven experience owning production systems with high availability requirements (≥99.99% uptime), including incident response, SLI/SLO/SLA definition, error budgets, and postmortems
• Hands-on experience designing and operating geo-replicated, multi-region, active-active systems, including traffic routing, failover strategies, and data consistency tradeoffs
• Strong experience building and owning observability components, including metrics, logging, and tracing (e.g., Prometheus, Grafana, OpenTelemetry).
• Experience with infrastructure as code (e.g., Helm, Terraform, Pulumi) and automated environment provisioning
• Strong understanding of system performance tuning, capacity planning, and resource optimization in distributed systems
• Experience implementing and operating security best practices in cloud-native environments (e.g., secrets management, network policies, vulnerability scanning)

Preferred:

• Experience operating data platforms or data-intensive workloads (e.g., Spark, Airflow, Kafka, Flink)
• Familiarity with service mesh technologies (e.g., Istio, Linkerd)
• Experience working in regulated environments with compliance frameworks such as GDPR, SOC 2, HIPAA, or SOX
• Background in building internal developer platforms or self-service infrastructure

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. 

• You love building highly reliable systems that operate at scale
• You’re curious about how to continuously improve system resilience, security, and operations
• You’re an expert in diagnosing and solving complex distributed systems problems

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 $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).

What You’ll Do:

The Platform & Infrastructure Engineering team in the Data Infrastructure organization is responsible for the performance, reliability, scalability, and security of the company’s data platform. The team builds and operates the foundational systems that power ingestion, transformation, analytics, and AI workloads at scale. This includes ownership of the underlying infrastructure for orchestration, compute, and storage systems that enable data engineering teams to build and deliver data products. We operate with production-grade discipline, supporting mission-critical services with stringent uptime requirements and a focus on automation, observability, and resilience.

About the role:

As an Engineering Manager, you will lead a team of Software Engineers and Site Reliability Engineers responsible for the infrastructure that powers CoreWeave’s data platform. You will own the reliability, scalability, and performance of core systems such as compute engines, orchestration frameworks, and storage layers. You’ll partner closely with Data Engineering teams, as well as cross-functional groups including Production Engineering, Developer Experience, Security Engineering, and IT Operations to ensure the platform is robust, secure, and easy to operate. This role balances people leadership with deep technical ownership, including stepping in hands-on when needed to support critical initiatives.

Who You Are: 

• 7+ years of experience in software engineering, infrastructure engineering, or data platform engineering roles
• 2+ years of experience managing engineering teams, including hiring, coaching, performance management, and career development
• Experience leading teams through the full software development lifecycle (SDLC), including planning, execution, and delivery of complex technical initiatives
• Experience running and evolving engineering processes (e.g., agile development, backlog management) to drive predictable execution and continuous improvement
• Experience setting team goals and metrics (e.g., OKRs) and holding teams accountable to outcomes
• Strong hands-on experience operating and scaling data platform infrastructure (e.g., Spark, Airflow, Iceberg, StarRocks) in production environments
• Deep expertise in Kubernetes and containerized software development, including cluster design, operations, and scaling in production environments
• Experience building and operating distributed systems with high availability and performance requirements, including SLOs and incident management
• Strong understanding of data platform architecture (compute, orchestration, storage) and experience driving reliability, performance, and cost optimization at the platform level
• Ability to contribute code and technical solutions when needed, with proficiency in at least one programming language (Python, Java, Go, Rust)
• Experience partnering with cross-functional engineering teams (e.g., Production Engineering, Developer Experience, Security, IT) and data engineering teams to deliver cohesive platform solutions

Preferred: 

• Experience supporting high-scale data workloads (e.g., large-scale Spark clusters, real-time ingestion platforms)
• Experience working in environments with strict uptime and reliability requirements (e.g., ≥99.99% uptime)
• Experience working in regulated environments with compliance frameworks such as GDPR, SOC 2, HIPAA, or SOX
• Experience building internal platforms that enable self-service analytics or developer productivity 

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. 

• You love building and leading teams that operate critical infrastructure at scale
• You’re curious about how to improve reliability, performance, and cost efficiency across complex data systems
• You’re an expert in navigating tradeoffs across platform architecture, system design, and engineering execution

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

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).

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard.
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Not located in Berlin? No worries, we offer extensive relocation support including allowances, one way flights, temporary accommodation and, by partnering with Expath, on the ground support on arrival
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Employee Equity Plan
• Generous professional development allowance
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• We offer free German courses at beginning, intermediate and advanced
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Comprehensive health benefits including medical, dental, and vision plans, as well as mental health resources
• Robust 401k program
• Employee Equity Plan
• Generous professional development allowance
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• 16 paid weeks for all parents (birthing and non-birthing), regardless of gender, to welcome newborns, adopted and foster children
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

About the Team

The DRW C/FICCO Data Engineering team is essential to developing valuable datasets and scalable data infrastructure critical to our trading operations. We work closely with traders, researchers, and other engineering teams to ensure seamless data flow and accessibility, supporting data-driven decision-making. Our systems are designed to handle large volumes of data, maintain quality and integrity, and provide robust APIs for fast, ergonomic data retrieval.

About the Role

In this role you will:

• Collaborate with cross-functional teams to deliver data solutions that support diverse trading activities.
• Take full ownership of data products, guiding them from initial concept through to stable production.
• Design, build, and maintain systems for both batch processing and real-time streaming of time series datasets, ensuring high data quality and reliability.
• Develop APIs and data access methods for fast, intuitive retrieval of historical and live data, working with both new and existing systems.
• Provide on-call support as needed.

Qualifications:

• A minimum of 2+ years’ experience using at least one of Python, Java, and C++, and can work comfortably in multiple programming languages
• A track record of working directly with end customers, scoping and delivering production systems in fast-moving and ambiguous environments
• Ability to dive deep into complex problems, develop intuitive understandings, spot risks early, and minimize complexity
• Exceptional interpersonal skills - you communicate clearly with stakeholders as well as other engineers, fostering a collaborative, supportive working environment
• Experience in the financial markets, especially in delta one, store of value, and/or FICC options trading
• Experience with Linux-based, concurrent, high-throughput, low-latency software systems
• Experience with pipeline orchestration frameworks (e.g. Airflow, Dagster)
• Experience with streaming platforms (e.g. Kafka), data lake platforms (e.g. Delta Lake, Apache Iceberg), and relational databases
• Have a Bachelors or advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or equivalent work experience

The annual base salary range for this position is $175,000 $225,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

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DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

As a Senior Data Engineer on our Data Experience team, you will play an integral role in bringing vendor datasets into our data platform, governing our centralized data pipelines, consolidating data delivery infrastructure across disparate systems, and working alongside individual Traders, Quantitative Researchers, and Back-Office personnel to best utilize the firm’s data and platform tools.

Technical requirements summary:

• Have extensive experience designing and building data pipelines
• Have experience working within modern batch and streaming data ecosystems
• An expert in SQL and Java or Python
• Extensive knowledge of data modeling techniques
• Able to own the delivery of data products, working with analysts and stakeholders to understand requirements and implement solutions
• Able to contribute to project management and project reporting
• Have experience driving nontrivial data migrations across platforms
• Able to establish, follow, and enforce data modeling standards across a large ecosystem.

What you will do in this role:

• Model, build, and manage data products built atop DRW’s Unified Data Platform.
• Work closely with Data Strategists to determine appropriate data sources and implement processes that onboard and manage new datasets for trading, research, and back-office purposes.
• Design data governance processes that enable discovery, cost-sharing, usage tracking, access controls, and quality control of datasets to address the needs of DRW trading teams and strategies.
• Continually monitor data ingestion pipelines and data quality to ensure stability, reliability, and quality of the data. Design monitoring and quality control software and processes.
• Own the technical aspects of vendor ingestion pipelines, coordinating with vendor relationship managers on upcoming changes, performing routine data operations without breaking internal users, and contributing to the team’s on-call rotation to respond to unanticipated changes.
• Rapidly respond to user requests, identifying platform gaps, and self-service opportunities that make the user experience more efficient.

What you will need in this role:

• 7+ years of experience working with modern data technologies and building data-first products.
• Excellent written and verbal communication skills.
• Proven ability to work in a collaborative, agile, and fast-paced environment, prioritizing multiple tasks and projects, and efficiently handle the demands of a trading environment.
• Proven ability to deliver rapid results within processes that span multiple stakeholders.
• Strong technical problem-solving skills.
• Extensive familiarity with SQL and Java or Python, with a proven ability to develop and deliver maintainable data transformations for production data pipelines.
• Experience leveraging data modeling techniques and ability to articulate the trade-offs of different approaches.
• Experience with one or more data processing technologies (e.g. Flink, Spark, Polars, Dask, etc.).
• Experience with multiple data storage technologies (e.g. S3, RDBMS, NoSQL, Delta/Iceberg, Cassandra, Clickhouse, Kafka, etc.) and knowledge of their associated trade-offs.
• Experience with multiple data formats and serialization systems (e.g. Arrow, Parquet, Protobuf/gRPC, Avro, Thrift, JSON, etc.).
• Experience managing data pipeline orchestration systems (e.g. Kubernetes, Argo Workflows, Airflow, Prefect, Dagster, etc.), delving deeply into low-level details.
• Proven experience in managing the operational aspects of large data pipelines such as backfilling datasets, rerunning batch jobs, monitoring event throughput, and handling dead-letter queues.
• Prior experience triaging data quality control processes, correcting data gaps and inaccuracies.

The annual base salary range for this position is $200,000 to $250,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

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