Senior Data Engineer

About the project We're recruiting for a project, where the team turns social media data (TikTok, Reddit and other platforms) into trend signals that feed the company's products. You'll join a small, senior data team. Your work is the data layer: pipelines, models, signal quality and new data sources. The dashboard UI is built by another team. What you'll do Extract, clean and model large social media datasets (posts, hashtags, engagement) from TikTok and other platforms Build and maintain dbt models and data pipelines, with automated tests for data quality Prototype pipelines and metrics for new data sources (starting with Reddit) and check whether they're useful Help map trend signals to new business categories (taxonomy, categorisation, validation) Work independently on scoped deliverables, document your work in Jira and write clean, reusable code Build quick prototypes to validate approaches with stakeholders What we're looking for 2+ years in a data engineering, analytics engineering or technical data analyst role (5+ years for Senior) Hands-on, commercial experience with dbt. You've built and tested models yourself, not just read about it Strong SQL: window functions, CTEs, deduplication, incremental logic Strong Python for data work: API extraction, data cleaning, pipeline scripting Experience with a cloud data warehouse. Snowflake is preferred; BigQuery, Redshift, Databricks or similar is fine for Mid Git in everyday work Comfortable working autonomously with limited onboarding Good English, as the whole team communicates in English You use AI coding tools (Copilot, Cursor, Claude Code etc.) and take full ownership of the output Nice to have Experience with social media or web data (TikTok, Reddit, Instagram, X) or public APIs Airflow or another orchestrator Data Vault modelling Trend or signal analysis: growth metrics, anomaly and bot detection, sentiment What we offer B2B contract, fully remote A data-heavy project with real product impact and a modern stack A small team with direct access to the Head of Data Quick recruitment process: a short call with us, a technical interview (dbt, SQL, Python) and a final interview with the project lead