Data Analytics Engineer (m/f/d)

Adsquare GmbH; Berlin; Vor Ort; EUR 60.000 - 75.000; Vollzeit

Benefits dieser Stelle

Flexible work models

1,200 € yearly education budget

30 vacation days

Urban Sports Club membership

Company pension scheme

Zusammenfassung

Adsquare GmbH is seeking a Data Analytics Engineer in Berlin to build and maintain production-grade data platforms. This role focuses on developing data workflows, writing scalable Python/SQL code, and optimizing cloud infrastructure.

Ideal candidates possess strong technical skills with a background in data engineering, and they will enjoy benefits like flexible work options, education budgets, and generous vacation days.

Qualifikationen

• 2+ years of experience in Analytics Engineering or Data Engineering.
• Ability to write modular, object-oriented Python code.
• Strong capability in building scalable data models.

Aufgaben

• Build, deploy, and maintain transformation pipelines for high-volume data.
• Optimize cloud costs by refactoring legacy systems.
• Focus on infrastructure monitoring and data quality.

Kenntnisse

Python proficiency

SQL & dbt

AWS Cloud Native Experience

Data Warehouse Ops knowledge

Ausbildung

B.S. or M.S. in Computer Science, Engineering, or Mathematics

Tools

Git

Docker

Terraform

Jobbeschreibung

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 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.

Your Mission

Key Responsibilities

• Pipeline Engineering: Build, deploy, and maintain robust transformation pipelines for high-volume data. 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, improving performance and reducing 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. 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.

Your Profile

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.

Must–Have Skills

• 2+ years of experience specifically in Analytics Engineering or Data Engineering.
• Solid Python proficiency: write modular, object‑oriented code, utilize relevant libraries for testing, and understand exception handling and logging.
• Strong skills in SQL & dbt: 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: build and maintain data workflows using serverless architectures such as AWS Lambda, Step Functions, Glue, and Athena.
• Testing Mindset: implement 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.

Nice to Have

• 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.)—helpful for debugging and monitoring but not core.
• B.S. or M.S. in Computer Science, Engineering, Mathematics or other relevant fields.

Benefits

• Open to flexible work models: hybrid mode and remote from anywhere in the world up to 3 months per year.
• Individual yearly budget of 1,200 € for education and professional growth.
• Entitled to 30 vacation days per year.
• Urban Sports Club membership, company pension scheme.
• Regular team events and company events organized by our People team.
• Equipped with the latest hardware and all tools needed to thrive.

Salary Range (Annual On-Target Earnings)

60,000 – 75,000 euros