Data Engineer – Analytics & Social Data

Requirements:

• 2+ years of commercial experience working with data.
• Strong hands-on experience with Python and SQL.
• Practical experience with dbt.
• Experience working with Snowflake.
• Experience cleaning, transforming, and working with large datasets.
• Good understanding of data quality and reliable data processing.
• Experience with Git/GitHub.
• Ability to independently deliver well-scoped technical tasks.

Nice to have:

• Experience with social media or web data.
• Experience working with external APIs and integrating new data sources.
• Experience with Airflow or another workflow orchestration tool.
• Familiarity with Data Vault modelling.
• Experience with Tableau and/or Power BI.
• Experience building prototype data pipelines.
• Experience defining or validating analytical metrics.
• Experience implementing automated tests for data transformations and pipelines.
• Previous exposure to trend or signal analysis.
• Experience evaluating the quality and usability of previously unknown datasets.
• Practical experience with AI coding tools such as Copilot, Cursor, Codex, or Claude Code.

About the Role

We are looking for a Data Engineer to work with large social and web datasets, helping transform raw data into reliable datasets, metrics, and insights. The role combines hands-on data work with data discovery, pipeline development, quality assurance, 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.

,[Extracting, cleaning, transforming, and analysing data from social and web sources., Building and improving data transformations and prototype pipelines., Working with large datasets and ensuring their quality and consistency., Supporting the evaluation of new data sources and developing metrics to assess their value., Identifying trends and meaningful signals within complex datasets., Applying automated testing to data pipelines and analytical outputs., Building quick prototypes to validate new data approaches with stakeholders., Producing clear analytical outputs and visualisations where needed., Writing clean, reusable code and documenting implemented solutions., Working independently on well-defined technical deliverables., Using AI-assisted development tools while maintaining ownership of code and data quality.] Requirements: Python, SQL, dbt, Snowflake, API, Airflow, Data Vault, Tableau, Power BI, AI Additionally: Sport subscription, Life insurance.