Data Engineer (Mid/Senior)

If your answer ticks all the boxes, this could be the start of a great collaboration.

• You have a curious mind - You won't understand what we're talking about if you don't.
• You want to learn more around technology - You won't survive if you don't.
• You want to make the world a bit better - We don't like you if you don't.

We happen to be just like that as well. We like hacking things here and there (you included) and create scalable solutions that bring value to the world.

Squaredev? ️

We use state-of-the-art technology to build solutions for our own customers and for the customers of our partners. We make sure we stay best-in-class by participating in research projects across Europe, collaborating with top universities and enterprises on AI, Data, and Cloud.

Role overview

We are looking for experienced Data Engineers to join our team and work on enterprise-scaledataand AI projects.

You will be part of projects built either on IBM Watson / Microsoft Fabric technologies or on Databricks-environments, collaborating closely with data scientists and software engineers to deliver AI-ready datasets and analytics solutions., * Designing and implementing data pipelines (batch and streaming) for analytics and AI workloads.

• Building and maintaining data lakes / warehouses (One Lake, BigQuery, Delta Lake, or any similar).
• Developing and optimizing ETL/ELT workflows using tools like Spark Jobs, dbt, Airflow or Prefect.
• Ensuring data quality, observability, and governance across all pipelines.
• Working closely with data scientists and software engineers to deploy and maintain AI-ready datasets.

Do you have experience in Terraform?, Do you have a Master's degree?, * At least 3 years of relevant work experience.

• Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
• Experience working in cloud platforms (e.g. MS Azure, AWS, GCP etc.).
• Hands-on experience with IBM Watson and/or BAW, or experience on Microsoft Fabric or Databricks projects.
• Strong experience in SQL and Python (PySpark or similar).
• Hands-on experience with data modeling, ETL frameworks and data orchestration tools.
• Familiarity with distributed systems and modern data platforms (Spark, Databricks, Fabric, Snowflake, or BigQuery).
• Understanding of data lifecycle management, versioning, and data testing.
• Solid grasp of Git and CI/CD workflows.
• Strong communication skills in English.

Nice to have:

• Knowledge of vector databases (pgvector, Pinecone, Milvus) or semantic search pipelines.
• Interest / knowledge in LLMs, AI pipelines.
• Familiarity with data catalogs, lineage tools, or dbt tests.
• DevOps familiarity (Docker, Kubernetes, Terraform).