[Hiring] Senior Data Engineer @Codurance

Role Description

We are looking for a Senior Data Engineer who shares our values of software craftsmanship, pragmatism, and professionalism. You understand that data engineering is, at its core, great software engineering, applied at scale, with rigor, 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 modernization, 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.

Qualifications

• Current or recent experience as a Data Engineer, Senior Data Engineer, Data Platform Engineer, or Databricks Engineer.
• 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, modernization 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.

Requirements

• Hands-on experience with Databricks in production.
• Strong experience with Python, testing, Git, CI/CD, code review, deployment, or Infrastructure as Code.
• Experience with data quality, orchestration, monitoring, lineage, schema evolution, or data contracts.
• Experience with client delivery, stakeholder engagement, modernization projects, mentoring, or working across engineering teams.
• Experience with AWS or Azure.
• Experience with ML/AI feature pipelines, MLflow, model lineage, embeddings, vector search, retrieval, or evaluation datasets.

Benefits

Company Description