Senior Data Engineer

As a Senior / Staff Data Engineer at The Product Counsel, you will design, build, and own robust data platforms that underpin analytics, reporting, and data-driven products for both TPC and our clients.

This is a senior, hands‑on role for engineers who care deeply about data correctness, trust, and long‑term sustainability. You will work across a variety of client environments, technologies, and cloud platforms, taking full ownership of data solutions end to end. You will collaborate closely with a Principal Data Engineer and other senior colleagues to shape standards, mentor others, and deliver high‑quality outcomes in complex, real‑world settings.

• Design, build, and maintain end‑to‑end data pipelines, from source systems through to analytics‑ready datasets.
• Own and improve ETL/ELT workflows, understanding how changes propagate across the data lifecycle.
• Design analytics‑ready data models that balance correctness, usability, and maintainability, applying patterns suited to data characteristics and downstream needs.
• Establish trusted data assets with clear ownership, shared definitions, and consistent behaviour across platforms.
• Take personal ownership of data quality, applying validation and reconciliation techniques to ensure outputs are accurate, explainable, and aligned with known business behaviour.
• Develop data solutions with clear lineage and traceability, mindful of downstream impact.
• Work with stakeholders (clients, analysts, product teams, and data scientists) to understand analytical needs and translate them into reliable, user‑focused data and reporting solutions.
• Contribute to and uphold engineering standards, best practices, and documentation.
• Review and evolve existing data platforms to improve performance, scalability, reliability, and maintainability.
• Support and mentor junior and mid‑level engineers at client sites, sharing expertise to elevate engineering quality within the client team.
• Participate in client‑facing discussions and business development activities as required, helping shape solutions and build trust with clients.

• Experience in Ad Tech or Mar Tech, with exposure to high‑volume, data‑intensive environments.
• Substantial hands‑on experience across data engineering, BI, or data platform roles, reflecting sustained exposure to real‑world systems.
• Proven track record of delivering accurate, trustworthy, production‑grade data solutions.
• Strong personal ownership and accountability for data quality.
• Comfortable operating autonomously in ambiguous environments and making sound technical decisions.

• Advanced SQL skills and extensive experience working with relational data at scale.
• Ability to design analytics‑ready data models that support historical accuracy, analytical performance, and evolving business needs.
• Experience designing, maintaining, and evolving end‑to‑end ETL/ELT pipelines, understanding how changes propagate downstream.
• Deep knowledge of data governance, data quality management, lineage, and impact analysis within complex data ecosystems.
• Skilled at reasoning critically about data behaviour over time and the downstream consequences of upstream design decisions.

• Experience with cloud data warehouses (e.g. Big Query, Snowflake, Redshift, ADW), including performance, cost, and data layout considerations.
• Proficiency with data integration and orchestration tools (e.g. Fivetran, Airflow, managed ELT platforms), and an understanding of how ingestion, transformation, and orchestration fit together.
• Experience building and maintaining an analytics or semantic modelling layer within reporting tools (e.g. Looker/LookML, Tableau, or similar), enabling consistent metrics,…