Senior Data Engineer AI - Portugal

Codurance · Portugal · posted Sep 28, 2026

Open to candidates in Portugal

Full-timesenior

You apply on the company's own site. We never charge to apply.

What this role actually asks for

Extracted by RemoteHunt

Must 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

DatabricksDelta LakeSparkPySparkUnity CatalogPythonGitCI/CDInfrastructure as CodeAWSAzureMLflow

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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