Senior Data Engineer AI - Portugal
Codurance · Portugal · posted Sep 28, 2026
Open to candidates in Portugal
You apply on the company's own site. We never charge to apply.
What this role actually asks for
Extracted by RemoteHuntMust have
- •Databricks in production (Delta Lake, Spark/PySpark, Unity Catalog)
- •Strong software engineering practices (Python, testing, Git, CI/CD)
- •Builds and operates reliable pipelines (data quality, orchestration, monitoring)
- •Client delivery and stakeholder engagement experience
- •Experience with modernization projects
Nice to have
- •AWS or Azure cloud experience
- •Experience with ML/AI feature pipelines
- •Experience with MLflow
- •Experience with vector search
Tools and technologies
The full posting
We are looking for a Senior Data Engineer who shares our values of software craftsmanship, pragmatism, professionalism. You understand that data engineering is, at its core, great software engineering, applied at scale, with rigour, and with production in mind. This is not a standalone data role.
You will work as part of our software delivery teams, helping clients build production-grade data foundations in broader modernisation, platform, data, and AI-readiness engagements. Databricks is our primary data engineering platform, and you will be expected to use it fluently; but the goal is always durable, well-crafted data systems, not tool advocacy. Current or recent
experience
Data Engineer, Senior Data Engineer, Data Platform Engineer, or Databricks Engineer role. Essential – Databricks in production Hands-on experience with Databricks in production, including Delta Lake, Spark/PySpark, Unity Catalog, or production lakehouse projects. Essential – Strong software engineering practices Strong experience with Python, testing, Git, CI/CD, code review, deployment, or Infrastructure as Code.
Essential – Builds and operates reliable pipelines Experience with data quality, orchestration, monitoring, lineage, schema evolution, or data contracts. Essential – Consulting and collaboration Experience with client delivery, stakeholder engagement, modernisation projects, mentoring, or working across engineering teams.
Preferred – Cloud Experience with AWS or Azure. Either cloud is acceptable for the role. Differentiator – Data for production ML/AI Experience with ML/AI feature pipelines, MLflow, model lineage, embeddings, vector search, retrieval, or evaluation datasets.
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