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Data Engineer – Analytics & Social Data

Skills

aiairflowapiclaude codedata pipelinesdata qualitydbtgitgithubpowerbiprototypingpythonsnowflakesqltableauvaultworkflow orchestration

Description

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.

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.

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