Senior Data Engineer

Team Leadership & People Management

Lead, manage, and grow a distributed team of data engineers (across North America and India) who report directly to you

AI-Assisted Development

• Champion the use of AI coding assistants (e.g., GitHub Copilot, Cursor, Claude) and prompt-based development to accelerate prototyping, code generation, refactoring, testing, and documentation.
• Establish best practices, guardrails, and review standards so the team uses these tools effectively and safely

Hands-On POCs & Prototyping

• Personally build proofs-of-concept to validate new tools and patterns (e.g., ClickHouse, dbt, open-source orchestration and pipeline frameworks) before broader rollout
• Translate the results into clear recommendations

Tech Stack Strategy & Architecture

Help shape the technical vision for our ETL and data platform. Evaluate, prototype, and recommend the technologies that will carry us forward, balancing flexibility, cost, performance, and avoiding vendor lock-in

Platform Modernization

• Drive the hands-on migration away from Azure Databricks toward a more open, flexible stack, minimizing disruption to our high-volume daily data delivery

Build & Own Pipelines

• Design, build, and optimize robust ETL pipelines that move and transform millions of daily data points reliably and efficiently

Deep System Integration

Master all systems upstream and downstream of your area, from ingestion through to client-facing platforms, to ensure seamless, high-quality, end-to-end data delivery

Operational Excellence

• Establish testing frameworks, QA plans, observability, and CI/CD practices that guarantee data integrity at scale

Technical Leadership Through Influence

Set technical standards and raise the bar across a distributed team (North America and India) through design guidance, code reviews, and mentorship — leading by expertise rather than direct people management

Domain Mastery

Rapidly learn the nuances of the Advertising and Market Research domain to translate business needs into robust technical requirements

Experience

• 8+ years in data engineering / ETL, with a strong track record as a hands-on engineer who has architected and built data platforms (Principal-level candidates will bring deeper architectural and cross-team impact)

AI-Assisted Engineering

• Hands-on experience using AI coding tools (e.g., GitHub Copilot, Cursor, Claude, or similar) and strong prompt-based development skills, with good judgment about where these tools help and where human review is essential

Core Databases

• Expert-level SQL and RDBMS skills with deep, hands-on experience in SQL Server and Postgres (schema design, performance tuning, complex query optimization, root-cause analysis)

Modern & Open-Source Stack

• Hands-on experience with technologies such as ClickHouse, dbt, and open-source data pipeline / orchestration tools (e.g., Airflow, Dagster, or similar), with the judgment to choose the right tool for the job

Cloud

• Strong, hands-on AWS experience is required, as we are standardizing on AWS as we move off Azure Databricks

POC & Evaluation Mindset

Demonstrated ability to independently prototype, benchmark, and evaluate new technologies and make pragmatic adoption decisions

Programming

• Strong proficiency in Python (or similar) for building and automating data pipelines

Education

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Bonus Points (Nice to Haves)

• Previous experience in Advertising, Media, or Market Research
• Familiarity with containerization (Docker, Kubernetes) and infrastructure-as-code
• Experience with streaming/real-time data technologies (e.g., Kafka)

Benefits

• Medical, Dental & Vision Insurance
• 401k with Company Match
• Flexible PTO
• Commuter Benefits
• Gym Discounts
• Summer Fridays