Senior Data Analytics Engineer; m​/f​/d

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.

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.

• 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.

• 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., Git Hub Actions, Git Lab CI), and Containerization (Docker). You understand how to deploy code reliably.

• AWS Cloud Native
  
  Experience:
  
  Hands‑on experience building serverless architectures using AWS Lambda, Step Functions, 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 Big Query), including partitioning, clustering, and cost governance.

• 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.

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