Berlin, Germany · Hybrid
$60k–$75k/yr
Intro At Adsquare, our mission is driven by our core focus: Passion – Solving complex challenges with great people, tech, and data. Niche – Location Intelligence for Programmatic Advertisers. Our core values are integral…
Skills: Python, SQL, dbt, AWS Lambda, AWS StepFunctions
Sign up with Clera and we'll reach out the moment a role actually fits you — no more spraying applications into the void.
Build and maintain robust data transformation pipelines and scalable workflows using a software engineering mindset. Focus on optimization, data quality observability, and the implementation of CI/CD workflows to ensure reliable cloud infrastructure.
Requires 2+ years of experience in Analytics or Data Engineering with strong proficiency in Python, SQL, and dbt. Must have hands-on experience with AWS serverless architectures, containerization, and software engineering fundamentals like automated testing.
At Adsquare, our mission is driven by our core focus: Passion – Solving complex challenges with great people, tech, and data. Niche – Location Intelligence for Programmatic Advertisers. Our core values are integral to everything we do:
Drive: We turn ambition into action.
Resilience: We adapt, persevere, and grow stronger.
No BS: We value honesty, transparency, and clear communication.
Humble: We choose modesty over vanity and let results speak for themselves.
Moral Compass: We do the right thing with fairness, integrity, and respect.
We seek candidates who not only bring excellent technical expertise but also embody these values in every aspect of their work.
Key Responsibilities
Pipeline Engineering: Build, deploy, and maintain robust transformation pipelines for high-volume data. You will participate in the full lifecycle: ingestion, transformation, testing (unit/integration), deployment, and monitoring.
Optimization & Maintenance: Write highly efficient code and collaborate with the team to refactor legacy systems, helping to improve performance and reduce cloud compute costs (e.g., optimizing Athena/Snowflake/Redshift clustering or AWS Glue jobs).
Software Engineering Best Practices: Adhere to and promote the team's technical standards by actively utilizing CI/CD workflows, containerization (Docker), and automated testing.
Data Quality & Observability: Focus on infrastructure monitoring rather than just business dashboards. You will implement alerts and checks (e.g., dbt tests, Great Expectations) to catch data quality issues before they reach stakeholders.
Collaboration & Growth: Work closely with Senior Engineers to plan architectures, participate actively in code reviews, and advocate for engineering rigor within the squad.
We are looking for a Data Analytics Engineer who approaches data with a software engineering mindset. You will join our Data Solutions squad to build and maintain production-grade data platforms.
This is not a Data Analyst role. While you will understand the business context, your primary focus is technical: building scalable workflows, writing clean and testable Python/SQL code, automating deployments, and supporting cloud infrastructure optimizations. You will ensure our pipelines remain reliable, cost-effective, and maintainable.
We are looking for a candidate who has solid analytics engineering experience or a strong background in backend development focused on data.
Must-Have Skills
2+ years of experience specifically in Analytics Engineering or Data Engineering.
Solid Python proficiency: You write modular, object-oriented code, utilize relevant libraries for testing, and understand exception handling and logging.
Strong skills in SQL & dbt: You can build scalable data models (Jinja templating, macros, incremental strategies) and understand query execution plans.
Software Engineering Fundamentals: Hands-on experience with Git flows, CI/CD pipelines (e.g., GitHub Actions, GitLab CI), and Containerization (Docker).
AWS Cloud Native Experience: Experience building and maintaining data workflows using serverless architectures such AWS Lambda, StepFunctions, Glue, and Athena.
Testing Mindset: Experience implementing Unit Tests and Integration Tests for data pipelines rather than relying solely on manual checks.
Data Warehouse Ops: Solid understanding of warehousing architecture (Snowflake, Redshift, or BigQuery), including partitioning and clustering concepts.
Experience with Infrastructure as Code (Terraform) to manage cloud resources.
Experience with orchestration tools like Airflow, Dagster, or Prefect.
Knowledge of big data processing frameworks (Spark/PySpark).
Experience with agentic coding CLI or IDE tools for more efficient planning, architecting and implementation of features.
Familiarity with dashboarding tools (Streamlit, Preset, Tableau, etc.) – Note: This is helpful for debugging and monitoring, but not the core function of the role.
B.S. or M.S. in Computer Science, Engineering, Mathematics or other relevant fields.
On top of a competitive package…
We are open to flexible work models: we work in a hybrid mode and remotely from anywhere in the world up to 3 months per year.
To encourage education and professional growth, we offer an individual yearly budget of 1.200€.
You are entitled to 30 vacation days per year.
We offer Urban Sports Club membership, company pension scheme.
Regular team events and company events organised by our People team (Trust us, they know how to throw a party!).
We equip you with the latest hardware and provide you with all the tools you need to thrive.
For technical roles (Data, Engineering, and Product), candidates are encouraged to upload any technical certifications referenced in their CV via the "Other Documents" section of the application form.
Alternatively, certification documents may be submitted after the first technical interview. Any certifications listed on the CV must be provided and successfully validated before proceeding to the second technical interview stage.
Step 1: Value-based interview (30 mins).
Step 2: Deep-dive technical interview (1.5 hours) with the Data team.
Step 3: Practical data-crunching challenge.
Step 4: Team Meet & Greet — the final step to ensure we're a great fit for each other.
Adsquare is the global audience & location intelligence company making marketing a whole lot smarter.
With eight offices around the world we are a truly international company but one united team working towards our vision: empowering companies to accelerate business growth by staying at the forefront of data-driven marketing.
Adsquare powers marketers with geospatial data science to enhance their omnichannel campaign experience.
Real-World Data for The Outcomes Era. Adsquare makes the physical world measurable — turning real-world behaviour into measurable business outcomes. We enable brands, agencies and platforms to plan, target, optimise and validate campaigns that close the online-to-offline gap. As a media-agnostic, Privacy-by-Design platform, we deliver intelligence they trust. Founded in 2012 and headquartered in Berlin, Adsquare operates across the Americas, Europe and APAC — trusted by over 2,500 clients across the globe. Discover more on our website.
Offices: Saarbrücker Str. 36, Berlin, Berlin 10405, DE · 14 Gray's Inn Road, London, England WC1X 8HN, GB · 40 rue du Colisée, Paris, Paris 75008, FR · 30 E 20th St, New York, 10003, US · Via Tortona, 33, Milan, Lombardy 20144, IT
Adsquare powers marketers with geospatial data science to enhance their omnichannel campaign experience.
Real-World Data for The Outcomes Era. Adsquare makes the physical world measurable — turning real-world behaviour into measurable business outcomes. We enable brands, agencies and platforms to plan, target, optimise and validate campaigns that close the online-to-offline gap. As a media-agnostic, Privacy-by-Design platform, we deliver intelligence they trust. Founded in 2012 and headquartered in Berlin, Adsquare operates across the Americas, Europe and APAC — trusted by over 2,500 clients across the globe. Discover more on our website.
Offices: Saarbrücker Str. 36, Berlin, Berlin 10405, DE · 14 Gray's Inn Road, London, England WC1X 8HN, GB · 40 rue du Colisée, Paris, Paris 75008, FR · 30 E 20th St, New York, 10003, US · Via Tortona, 33, Milan, Lombardy 20144, IT
