Senior Data Engineer (Python, Databricks)

Keystone AI 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 Employment type: 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 Employment conditions: B2B contract, Daily support from team leaders, Dedicated certification budget, Assistance in defining and support in your development path, Benefits package, Integration trips/events.