Senior Data Analytics Engineer (m/f/d) at adsquare GmbH

Berlin, , Germany -

Full Time

Start Date

Immediate

Expiry Date

13 Aug, 26

Salary

0.0

Posted On

15 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, dbt, AWS, Docker, CI/CD, Data Modeling, Unit Testing, Integration Testing, Snowflake, Redshift, BigQuery, AWS Lambda, AWS Glue, AWS Athena, Git

Industry

Software Development

Description

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 top-tier technical expertise but also embody these values in every aspect of their work. About the team Your Mission Key Responsibilities End-to-End Pipeline Engineering: Design and deploy robust transformation pipelines for high-volume data (TB scale). You are responsible for the full lifecycle: ingestion, transformation, testing (unit/integration), deployment, and monitoring. Architecture & Optimization: Take ownership of data modeling and architectural decisions. You will actively refactor legacy code to improve performance and reduce cloud compute costs (e.g., optimizing Athena/Snowflake/Redshift clustering or AWS Glue jobs). Software Engineering Best Practices: Elevate the team's technical standards by implementing CI/CD workflows, containerization (Docker), and rigorous automated testing. You ensure that "it works on my machine" is never an excuse. Data Quality & Observability: Instead of just building business dashboards, you build infrastructure monitoring. You will implement alerts and checks (e.g., dbt tests, Great Expectations) to catch data quality issues before they reach stakeholders. Technical Leadership: Mentor junior engineers through code reviews and technical planning. You will be the voice of engineering rigor within the squad. Your Profile We are looking for a Senior Data Analytics Engineer who approaches data with a software engineering mindset. You will join our Data Solutions squad to architect, 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: designing scalable architectures, writing clean and testable Python/SQL code, automating deployments, and optimizing cloud infrastructure. You will act as a technical standard-bearer, ensuring our pipelines are reliable, cost-effective, and maintainable. We are looking for a candidate who has strong analytics engineering experience or has a strong background in backend development focused on data. Must-Have Skills 4+ years of experience specifically in Analytics Engineering or Data Engineering. Advanced Python proficiency beyond scripting: You write modular, object-oriented, and production-ready code. You use relevant libraries and framework for testing, and understand exception handling and logging. Deep expertise in SQL & dbt: You don't just write queries; you build scalable data models (Jinja templating, macros, incremental strategies) and understand query execution plans to optimize performance. Software Engineering Fundamentals: Proven experience with Git flows, CI/CD pipelines (e.g., GitHub Actions, GitLab CI), and Containerization (Docker). You understand how to deploy code reliably. AWS Cloud Native Experience: Hands-on experience building serverless architectures using AWS Lambda, StepFunctions, Glue, and Athena. Testing Mindset: You can demonstrate experience implementing Unit Tests and Integration Tests for data pipelines. You do not rely on manual checks or stakeholder validation for quality assurance. Data Warehouse Ops: Deep understanding of warehousing architecture (Snowflake, Redshift, or BigQuery), including partitioning, clustering, and cost governance. Nice-to-Have Skills 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). Familiarity with dashboarding tools (Streamlit, Preset, Tableau e.t.c) – 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. What you will do Nice to Have Our Software Stack Why us? On top of a competitive package… We are open to flexible work models: we work on 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 Salary Range (Annual On-Target Earnings) Recruiting Process Work model Desired start date About us 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. We are pioneers in advertising and data. We were born mobile, before it was a necessity, and have pioneered data-driven advertising in display and now DOOH. We have the smartest people, working with the best tech, so we can drive the pace of change. We are visionaries. We see a better way for marketers and are doing everything we can to make that a reality. We believe in innovation and the power of technology. We believe in constantly improving what we’re doing because the work is never done. We believe in what we do and rise to meet our own high standards. If there’s a problem, we fix it, humbly and without fuss or delay. Although our technology is best-of-breed, we are unassuming and modest in our approach. We are passionately candid, both with each other and with our clients. We take the time to explain our approach to their problem, confident there is nothing to hide. We are consistent and true to our word. We don’t take shortcuts but focus on being our clients’ most reliable partner. We make promises - and we keep them. As a result, clients enjoy spending time with us, because we are good people.

Responsibilities

Design and deploy robust end-to-end data transformation pipelines for high-volume data while optimizing cloud compute costs. Implement software engineering best practices including CI/CD, containerization, and rigorous automated testing for data quality and observability.