Senior Data Engineer (Python, Databricks)

Craftware is a technology company of over 500 experts, empowering large organizations to solve complex business challenges with modern IT solutions - from sales systems and automation to data platforms and AI. We operate where technology must be reliable, secure, and scalable. We deliver end-to-end projects: from analysis and architecture through implementation to development and maintenance. We are a trusted partner of industry leaders such as Salesforce, Veeva, UiPath, and Databricks.

Model: remote

Engagement:: full-time

Responsibilities

• Build and maintain DAB pipelines and YAML-based transformation configuration; migrate toward native Databricks Asset Bundle patterns

• Keep DEV / QAS / PRD environments consistent and drift-free across delivered markets

• Assess new data sources before sprint commitment — shape, volume, quality risks — and write feasibility notes that gate scope entry

• Develop PySpark transformations across Raw, Quality Integration, and Curated zones following CDA layer standards

• Define and run data reconciliation and acceptance criteria so business users aren't the primary quality gate at UAT

Requirements

• Azure Databricks & PySpark — senior hands-on: jobs, clusters, Unity Catalog, transformation logic, unit testing

• Delta Lake — schema evolution, MERGE, time travel; DAB — YAML config and bundle deployment

• SQL — advanced; able to read 10-year-old stored procedures without help

• CI/CD — Azure DevOps, Git branching strategy, PR discipline — practised, not theoretical

• Ability to profile source data, define acceptance criteria, and take a data problem from source assessment to UAT sign-off — without a BA intermediary

• Comfortable with incomplete documentation and evolving scope — you document decisions so others don't need a handover call

We offer:

• B2B contract

• Fully remote service delivery

• Broad range of projects (internal, international) - genuine variety of clients and tasks

• Budget for skills development and certifications as part of the collaboration

• Regular collaboration reviews and discussion of project scope

• Additional benefits available as part of the collaboration

• Networking and team-building events for project teams

Tech stack

• Python
• PySpark
• Databricks
• SQL
• CI/CD