Senior Data Engineer

Role Description

We are looking for a highly technical, hands-on Senior Data Engineer to drive the evolution of our data delivery platform while leading a team of data engineers. This is a player-coach role:

• Architect our next-generation data stack.
• Build proofs-of-concept (POCs) and prove out new technologies before committing to them at scale.
• Manage and grow a team of engineers who report directly to you.
• Partner closely with engineering leadership to shape the technical direction of our pipelines while staying hands-on in the systems.

We are deliberately moving away from a locked-in, vendor-heavy stack toward a flexible, largely open-source architecture that keeps our options open. We expect our engineers to work in a modern, AI-assisted way:

• Use AI coding tools and prompt-based workflows to move faster without compromising quality.
• Evaluate tools, build POCs, and make pragmatic, evidence-based decisions about what we adopt next.

This is a build-and-prove role:

• Write code, design schemas, profile queries, and understand the "how" and "why" behind every pipeline.
• Mentor your team to do the same.

• Team Leadership & People Management: Lead, manage, and grow a distributed team of data engineers (across North America and India).
• AI-Assisted Development: Champion the use of AI coding assistants and prompt-based development.
• Hands-On POCs & Prototyping: Build proofs-of-concept to validate new tools and patterns.
• Tech Stack Strategy & Architecture: Help shape the technical vision for our ETL and data platform.
• Platform Modernization: Drive the migration away from Azure Databricks toward a more open, flexible stack.
• Build & Own Pipelines: Design, build, and optimize robust ETL pipelines.
• Deep System Integration: Master all systems upstream and downstream to ensure seamless data delivery.
• Operational Excellence: Establish testing frameworks, QA plans, observability, and CI/CD practices.
• Technical Leadership Through Influence: Set technical standards and raise the bar across a distributed team.
• Domain Mastery: Rapidly learn the nuances of the Advertising and Market Research domain.

Qualifications

• 8+ years in data engineering / ETL, with a strong track record as a hands-on engineer.
• Hands-on experience using AI coding tools and strong prompt-based development skills.
• Expert-level SQL and RDBMS skills with deep experience in SQL Server and Postgres.
• Hands-on experience with technologies such as ClickHouse, dbt, and open-source data pipeline tools.
• Strong, hands-on AWS experience.
• Demonstrated ability to independently prototype, benchmark, and evaluate new technologies.
• Strong proficiency in Python (or similar) for building and automating data pipelines.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Requirements

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

Benefits

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