Senior Data Engineer

About the project

We're recruiting for a project, where the team turns social media data (Tik Tok, 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.

• Extract, clean and model large social media datasets (posts, hashtags, engagement) from Tik Tok 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

• 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;
  Big Query, 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

• Experience with social media or web data (Tik Tok, Reddit, Instagram, X) or public APIs
• Airflow or another orchestrator
• Data Vault modelling
• Trend or signal analysis: growth metrics, anomaly and bot detection, sentiment

• 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