Senior Data Engineer

About the Role

We are looking for an experienced Senior Data Engineer to take technical ownership of data solutions built around large-scale social and web data. The role combines hands-on engineering, data discovery, metric development, data quality, and rapid prototyping.

What we offer:

• Fully remote work.
• High level of technical ownership and autonomy.
• Real influence on how new data sources, metrics, and technical approaches are developed.
• Hands-on work with Python, SQL, dbt and Snowflake.
• Opportunity to solve technically complex problems using large and diverse datasets.
• Opportunity to combine engineering with experimentation, data discovery, and rapid prototyping.
• Close collaboration with senior data leadership.
• Opportunity to shape engineering and data quality practices within the workstream.
• Access to modern AI-assisted development tools.
• Multisport card.
• Private healthcare.

Requirements:

• 5+ years of commercial experience in data engineering, analytics engineering, or another strongly technical data role.
• Strong hands-on experience with Python and SQL.
• Strong practical experience with dbt.
• Experience working with Snowflake.
• Experience building or developing reliable data pipelines and transformations.
• Strong understanding of data quality and automated testing.
• Ability to independently own complex technical problems from definition through implementation.
• Experience translating business or product requirements into technical solutions.
• High level of autonomy, technical judgement, and ownership.

Nice to have:

• Experience working with social media, web, trend, or behavioural data.
• Experience integrating external APIs and new data sources.
• Experience with Airflow or other orchestration tools.
• Experience with Data Vault modelling.
• Experience with Tableau and/or Power BI.
• Broader experience with data modelling and data warehouse concepts.
• Experience designing analytical metrics and data products.
• Experience building prototypes to validate new data approaches.
• Experience introducing automated data quality checks and testing practices.
• Experience assessing unfamiliar datasets for quality and business value.
• Previous exposure to trend or signal analysis.
• Practical experience with AI coding tools such as Copilot, Cursor, Codex, or Claude Code.