Sr. Data Engineer

Our Senior Data Engineer is a hands-on, client-facing technical lead. You’ll own data pipelines and integrations for several clients ’ll step into established client work, get up to speed quickly, and keep delivery moving while improving what’s already there.

You’ll be the trusted technical voice with clients. That means translating their business goals into data solutions, setting clear expectations on scope and effort, and bringing a point of view on how their data should work for them.

This is an individual contributor role reporting to the SVP of Tech and Data. You’ll lead through expertise and influence rather than direct reports, keeping engineering work on agreed architectural paths.

We’re looking for a modern-day ETL/ELT developer who works comfortably in today’s analytical environment and understands the marketing landscape, where disparate data is everywhere. You build with AI-assisted coding tools every day and help the team use them well. We do whatever it takes to solve problems, while embracing change each day.

What you will doLead client work

Own data engineering for multiple clients and projects at once, from requirements through delivery and ongoing support

Work directly with clients to understand their business goals, and give them a clear, specific point of view Negotiate scope and level of effort with clients and internal teams so everyone agrees on what gets delivered and when Collaborate closely with analysts, engineers and managers across the agency

Look past day-to-day tasks to the business results the work needs to deliver

Build and own data platforms

Design, build and maintain data pipelines and integrations with complex source data and API services

Take ownership of established client pipelines: reverse engineer existing SQL and pipeline code to understand its business logic, and document it as you goMove and model data across platforms using established ETL/ELT patterns, orchestrated with Apache Airflow Recommend and design database solutions, and handle performance tuning, troubleshooting and capacity estimation

Keep engineering work on agreed architectural paths and follow our data warehouse development standards

Maintain documentation for data movement and transformation processes, including process flows and data mapping

Manage priorities, access and quality

Set priorities for your projects and tasks, and push back when needed to protect the right priorities and workflow

Set the criteria for who is added to or removed from client data services and systems

Create and manage audit reporting and quality checks so data is delivered accurately and consistently

Solve problems

Identify challenges and limitations in the tools we use, and propose fixes

Spot roadblocks early that could affect deadlines

Break complex work into clear tasks and coordinate them with the team

Work with teammates and external partners to troubleshoot quickly and keep delivery on track

Stay ahead

Use AI coding assistants as a core part of your development work, and contribute to the team’s AI best practices

Identify relevant new technology and share what you learn with the team

What you should have Bachelor’s degree or equivalent combination of education and experience preferred, in computer science or information systems4–5+ years of hands-on data engineering experience

Experience with RDBMS and cloud data warehouses such as PostgreSQL, SQL Server, Snowflake and Google BigQueryETL/ELT development in SQL and Python, with orchestration in Apache Airflow; familiarity with dbt is helpful

Experience with AWS and GCP, with strong hands-on experience in at least one Advanced SQL, including stored procedures, indexing and database IO performance tuning

Solid understanding of data warehouse design principles and…