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:
- 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 Role
As a (Senior) Data Engineer at Adsquare, you will be a key contributor to our core engineering function, creating and maintaining scalable big data pipelines that power our applications and drive business value. Because our engineering department handles a variety of critical data challenges, you will be assigned to a specific cross‑functional squad based on your individual strengths, experience, and current business needs.
Responsibilities
- Data Pipeline Ownership: Take full accountability for the pipeline lifecycle—from raw data ingestion to transformation and external delivery—according to defined SLAs, time, and budget.
- Architect Scalable Solutions: Design and build robust data architectures required to process and transfer terabytes of data.
- Pipeline Optimization: Continuously improve data pipelines for cost and performance. This includes analyzing query plans, optimizing compute and working memory, and strategically applying horizontal or vertical scaling.
- Engineering Rigor: Elevate data engineering standards. Implement CI/CD workflows, infrastructure‑as‑code, test‑driven development (TDD), and automated testing to ensure reliable and maintainable code.
- Data Monitoring: Create and maintain live monitoring dashboards to ensure data solutions are healthy and to support strategic decision‑making.
- Collaboration & Mentorship: Bridge the gap between Data and Backend engineering. For Senior applicants, act as a technical leader by mentoring junior team members, conducting code reviews, and introducing best practices.
Qualifications
We are looking for a candidate with varying levels of experience (mid‑level to senior, typically 3‑6+ years) in Data Engineering or Backend Development with a heavy data focus. You must be comfortable working in a self‑organized, agile environment.
Required Skills
- Programming Mastery: Very strong proficiency in Python and SQL. You write modular, production‑ready code and possess a solid understanding of both Functional Programming and Object‑Oriented Programming (OOP) principles.
- Big Data & PySpark: Deep experience with large‑scale data processing frameworks, specifically Apache Spark / PySpark. You understand how to handle TB‑scale datasets efficiently. Deep understanding of big data file formats like parquet and avro. Experience with open Lakehouse formats like Iceberg.
- Advanced Optimization Skills: Proven experience in optimizing data pipelines for compute, working memory, and cost efficiency, including reading and analyzing complex query plans/profiles.
- Database & Storage Architecture: Expertise in the trade‑offs between OLAP and OLTP systems. You have built solutions using relational and non‑relational (NoSQL) databases, and horizontally scalable data warehouses/lakehouses (e.g., Redshift, Snowflake, StarRocks).
- Cloud Native (AWS): Experience architecting solutions within the AWS ecosystem (e.g., S3, Athena, Glue, EMR, Lambda, Batch).
- Infrastructure & Orchestration: Production experience treating infrastructure as software using Terraform, alongside experience with orchestration tools like Airflow, dbt, or Step Functions.
- Engineering Fundamentals: Solid grasp of computer science principles, data structures, algorithms, and git‑flow/CI/CD pipelines.
- AI tools: Good command of using AI tools (e.g. Claude Code, Kiro, Gemini Pro) to improve and refactor your code, increase your productivity and quality and performance of your code.
Preferred Skills
- Compiled Languages: Experience with a compiled or strongly typed language (e.g., Java, Scala, Go, Kotlin, C++, Cython).
- Geospatial Data: Experience working with GIS (Geographic Information Systems) and geo‑spatial datasets.
- Data Formats: Expertise in optimizing file formats (Parquet, Avro, Iceberg) for performance.
- Streaming Technologies: Familiarity with Kafka and Flink.
- Backend Context: Experience working closely with Backend engineers or familiarity with Backend architectural patterns (microservices, API design).
Pay range and compensation package
On top of a competitive package, we offer:
- Hybrid work model + remote work from anywhere worldwide up to 3 months/year
- Individual yearly learning budget of 1,200€
- 30 vacation days per year
- Urban Sports Club membership
- Company pension scheme
- Regular team and company events
- Latest hardware and all tools you need to thrive
Equal Opportunity Statement
We are committed to diversity and inclusivity.
