Senior Data Engineer

Role Requirements

We are seeking a pragmatic and skilled Data Scientist to join The Product Counsel team, working remotely with a preference for candidates based in London or Cambridge. In this role, you'll harness the power of vast advertising datasets to develop, evaluate, and deploy machine learning models that drive real business impact. You'll collaborate closely with a dedicated data engineer, allowing you to focus on modelling, mathematics, and delivering actionable insights—but if you’re eager to get hands-on across the stack, we encourage and support that, too!

What You’ll Do

• 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.
  
  

What We’re Looking For

Experience & Mindset

• 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.
  
  

Core Data Engineering Skills

• 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.
  
  

Modern Data Stack

• Experience with cloud data warehouses (e.g. BigQuery, 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, intuitive drill paths, and flexible data exploration.
• Clear understanding of how data models, transformations, and reporting layers work together to support reliable, user-focused analytics.
• Experience working with at least one major cloud platform (AWS, GCP, Azure, or OCI).
• Programming experience in Python (or similar) for data engineering tasks.
  
  

Ways of Working

• Effective communicator who can explain complex data concepts clearly to technical and non-technical audiences.
• Experienced in collaborating directly with stakeholders and clients.
• Comfortable balancing delivery, quality, and long-term maintainability.
• Willing to contribute to business development activities and support company growth when needed.
  
  

Location & Benefits

Remote role with a preference for candidates based in London or Cambridge

• Flexible working hours and a collaborative, supportive team culture
• Opportunity to work on impactful, high-visibility projects in the advertising technology space