About the Client & Role Overview

Our client is a data-first performance marketing agency helping businesses achieve measurable growth through smarter media, analytics, and automation. They are in the process of strengthening their ETL and data infrastructure to support more intelligent decision-making, spanning creative analytics, predictive modeling, and AI-augmented planning.

This is a hands-on leadership role where you’ll guide the ongoing optimization of ETL infrastructure while also influencing broader platform improvements. You’ll work closely with analysts, engineers, and leadership to ensure pipelines are reliable, efficient, and structured for long-term scale. This includes helping formalize data governance practices, evolving a light semantic layer, and enabling greater downstream automation of analysis and AI use cases.

What You’ll Do

• Take ownership of pipeline stability and performance across the GCP-based stack (BigQuery, GCS, Dataprep/Dataflow)
• Lead the enhancement of existing ETL workflows to support better modularity, reusability, and error handling
• Help introduce lightweight governance practices—including column-level validation, source tracking, and transformation transparency
• Support development of a semantic layer (e.g., KPI definitions, normalized metric naming) to reduce rework and support downstream users
• Work with analysts and dashboard developers to structure data outputs for intuitive use and parameterization
• Collaborate with team leadership to prioritize improvements based on impact and feasibility
• ●​Support platform readiness for automated reporting, predictive modeling, and AI-enhanced analysis
• Contribute to team culture through clear documentation, mentoring, and code review
• Participate in hiring, onboarding, and evolving internal standards

What We’re Looking For

• 7+ years of experience in data engineering, preferably in a fast-paced agency or multi-client environment
• Solid command of Google Cloud Platform, especially BigQuery, GCS, and Cloud Dataprep (Alteryx) or Dataflow
• Strong SQL and Python skills with a focus on transformation and data reliability
• Experience building and maintaining ETL pipelines in production
• Familiarity with metadata-driven development, version control, and task orchestration (Airflow or equivalent)
• Proven ability to balance individual execution with team collaboration
• Clear communicator, able to translate technical trade-offs to non-technical stakeholders

Nice-to-Have

• Experience applying basic data governance principles (e.g., lineage tracking, validation frameworks, naming conventions)
• Exposure to building or maintaining a semantic layer (via dbt, LookML, etc.)
• Familiarity with AI/ML workflows or tooling for automated insight generation
• Understanding of marketing or media datasets
• Experience developing custom marketing attribution models
• Experience mentoring junior team members or participating in code/process standardization