Lead Data Software Engineer with Cloud Services and Databricks

EPAM Systems; Deutschland; Vor Ort; EUR 70.000 - 105.000; Vollzeit

Zusammenfassung

EPAM Systems in Germany is hiring a Data Engineer to lead the full engineering lifecycle for process mining use cases, from discovery to production support. You will design and develop scalable Databricks components and Apps, and mentor engineers in testing, CI/CD, and code reviews.

The role emphasizes AI-enabled SDLC, data governance, security, and collaboration with architects and stakeholders. English at B2+ is required; German language skills are a plus.

Qualifikationen

• 5+ years of hands-on experience with Python and data engineering.
• Experience designing and implementing data ingestion and transformation pipelines.
• Practical experience with Databricks, data modeling, data quality, and source-system integration.
• Knowledge of, and ideally practical experience building and deploying, Databricks Apps.
• Experience delivering data or analytics use cases through the complete development lifecycle.
• Familiarity with AI-native ways of working and AI tools such as GitHub Copilot, Databricks Genie, and Claude Code.
• Experience establishing engineering processes, CI/CD, testing, code review, and release practices.
• Demonstrable hands-on experience using AI tools across the SDLC.
• Ability to critically review and validate AI-generated code, tests, designs, and documentation.
• Experience mentoring engineers and enabling knowledge sharing.
• Proactive, independent working style with strong communication and stakeholder-management skills.
• Awareness of data governance, security, compliance, data lineage, and privacy requirements.
• Proficiency in English at a B2+ level

Aufgaben

• Lead the full engineering lifecycle for process mining use cases, from discovery to production support.
• Analyze source systems and implement reliable data ingestion, transformation, and validation pipelines.
• Design and develop scalable, reusable Databricks components and Databricks Apps.
• Lead PoC migrations from Celonis, assess feasibility, and evolve successful solutions into production.
• Establish team engineering practices covering development, unit and integration testing, code review, CI/CD, deployment, and monitoring.
• Identify technical risks and dependencies, make design decisions, and collaborate with architects and stakeholders.
• Apply AI tools across the SDLC, including requirements analysis, coding, testing, code review, documentation, troubleshooting, and knowledge transfer.
• Ensure AI-assisted outputs meet quality, security, compliance, confidentiality, and maintainability standards.
• Support engineers through code reviews, documentation, reusable patterns, and knowledge-transfer sessions.
• Provide technical input to requirements, acceptance criteria, and delivery planning.

Kenntnisse

Python

Data engineering

Data ingestion

Data transformation

Data modeling

AI tools

Mentoring

CI/CD

Stakeholder mgmt

Tools

Databricks

Databricks Apps

GitHub Copilot

Databricks Genie

Claude Code

Jobbeschreibung

Responsibilities

• Lead the full engineering lifecycle for process mining use cases, from discovery to production support
• Analyze source systems and implement reliable data ingestion, transformation, and validation pipelines
• Design and develop scalable, reusable Databricks components and Databricks Apps
• Lead PoC migrations from Celonis, assess feasibility, and evolve successful solutions into production
• Establish team engineering practices covering development, unit and integration testing, code review, CI/CD, deployment, and monitoring
• Identify technical risks and dependencies, make design decisions, and collaborate with architects and stakeholders
• Apply AI tools across the SDLC, including requirements analysis, coding, testing, code review, documentation, troubleshooting, and knowledge transfer
• Ensure AI-assisted outputs meet quality, security, compliance, confidentiality, and maintainability standards
• Support engineers through code reviews, documentation, reusable patterns, and knowledge-transfer sessions
• Provide technical input to requirements, acceptance criteria, and delivery planning

Requirements

• 5+ years of hands-on experience with Python and data engineering
• Experience designing and implementing data ingestion and transformation pipelines
• Practical experience with Databricks, data modeling, data quality, and source-system integration
• Knowledge of, and ideally practical experience building and deploying, Databricks Apps
• Experience delivering data or analytics use cases through the complete development lifecycle
• Familiarity with AI-native ways of working and AI tools such as GitHub Copilot, Databricks Genie, and Claude Code
• Experience establishing engineering processes, CI/CD, testing, code review, and release practices
• Demonstrable hands-on experience using AI tools across the SDLC
• Ability to critically review and validate AI-generated code, tests, designs, and documentation
• Experience mentoring engineers and enabling knowledge sharing
• Proactive, independent working style with strong communication and stakeholder-management skills
• Awareness of data governance, security, compliance, data lineage, and privacy requirements
• Proficiency in English at a B2+ level