<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p><strong>Intro:</strong></p><p><br/></p><p>At Adsquare, our mission is driven by our core focus:</p><p><br/></p><p><strong>Passion</strong> – Solving complex challenges with great people, tech, and data.</p><p><strong>Niche</strong> – Location Intelligence for Programmatic Advertisers.</p><p><br/></p><p>Our core values:</p><p><br/></p><ul><li><strong>Drive</strong> – We turn ambition into action</li><li><strong>Resilience</strong> – We adapt, persevere, and grow stronger</li><li><strong>No BS</strong> – We value honesty, transparency, and clear communication</li><li><strong>Humble</strong> – We let results speak for themselves</li><li><strong>Moral Compass</strong> – We do the right thing with fairness, integrity, and respect</li></ul><p><br/></p><p><strong>Your Mission</strong></p><p><br/></p><p>You will join our Data Solutions squad to build and maintain production-grade data platforms. This is not a Data Analyst role — your primary focus is technical: building scalable workflows, writing clean and testable Python/SQL code, automating deployments, and supporting cloud infrastructure optimisations.</p><p><br/></p><p><strong>Key Responsibilities</strong></p><p><br/></p><ul><li>Build, deploy, and maintain robust transformation pipelines for high-volume data (full lifecycle: ingestion, transformation, testing, deployment, monitoring)</li><li>Write highly efficient code and refactor legacy systems to improve performance and reduce cloud compute costs (Athena, Snowflake, Redshift, AWS Glue)</li><li>Adhere to and promote CI/CD workflows, containerisation (Docker), and automated testing</li><li>Implement data quality alerts and checks (dbt tests, Great Expectations) before issues reach stakeholders</li><li>Work closely with Senior Engineers on architecture planning, code reviews, and engineering rigour</li></ul><p><br/></p><p><strong>Must-Have Skills</strong></p><p><br/></p><ul><li>2+ years in Analytics Engineering or Data Engineering</li><li>Solid Python proficiency (modular, OOP, testing libraries, exception handling, logging)</li><li>Strong SQL &amp; dbt skills (Jinja templating, macros, incremental strategies, query execution plans)</li><li>Git flows, CI/CD pipelines (GitHub Actions / GitLab CI), Docker</li><li>AWS Cloud Native: Lambda, StepFunctions, Glue, Athena</li><li>Unit &amp; Integration testing for data pipelines</li><li>Data warehouse architecture: Snowflake, Redshift, or BigQuery (partitioning &amp; clustering)</li></ul><p><br/></p><p><strong>Nice to Have</strong></p><p><br/></p><ul><li>Terraform (Infrastructure as Code)</li><li>Orchestration tools: Airflow, Dagster, or Prefect</li><li>Big data frameworks: Spark / PySpark</li><li>Agentic coding CLI/IDE tools</li><li>Dashboarding: Streamlit, Preset, Tableau</li><li>B.S./M.S. in Computer Science, Engineering, or Mathematics</li></ul><p><br/></p><p><strong>Yearly OTE: </strong>€60,000 – €75,000</p><p><br/></p><p><strong>What We Offer</strong></p><p><br/></p><ul><li>Hybrid + remote from anywhere up to 3 months/year</li><li>€1,200 yearly learning &amp; development budget</li><li>30 vacation days</li><li>Urban Sports Club membership + company pension scheme</li><li>Latest hardware provided</li><li>Regular team &amp; company events</li></ul><p><br/></p><p><strong>Recruiting Process</strong></p><p><br/></p><ol><li>Value-based interview (30 min)</li><li>Deep-dive technical interview (1.5 hrs) with the Data team</li><li>Practical data-crunching challenge</li><li>Team Meet &amp; Greet</li></ol><p><br/></p><p>Berlin | Hybrid | Start: ASAP</p> </div>