EPAM Systems
Senior AI Engineer, Databricks
Builds Databricks-based data engineering frameworks and AI-ready pipelines, enabling teams to create scalable data products and integrate AI agents with CI/CD and Lakehouse best practices.
- Compensation
- Not disclosed
- Location
- Kazakhstan
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 3+ years of experience in Data Engineering with a proven track record of building enterprise-quality Data Products, preferably in Lakehouse architecture
- Proficiency in Python development
- Proficiency in version control systems such as GitHub and CI/CD frameworks such as GitHub Actions
- Strong knowledge of Databricks technologies including PySpark, Delta Lake, and Unity Catalog, or equivalent technology
- Strong knowledge in Agentic AI and frameworks such as LangGraph, MCP, and A2A
- Strong knowledge of industry-standard microservices technologies including Kubernetes and Docker
- Strong English communication skills, both written and spoken, for collaboration with international teams
- Ability to provide actionable technical guidance and implement engineering excellence practices among agile team peers
Full description
We are seeking a Senior AI Engineer, Databricks, to design and build the data engineering framework, reusable components, and best practices that empower hundreds of SAP Data Engineers to create AI-ready Data Products at scale, while extending this framework for AI Agent consumption and enhancing the developer experience through AI-assisted tooling.
Responsibilities
- Design and build data engineering frameworks, reusable components, and templates such as CI/CD pipelines to boost productivity across data engineering teams
- Establish best practices for building AI-ready Data Products with enterprise-grade quality
- Extend the data engineering framework to enable AI Agents to discover and consume Data Products at scale
- Develop and integrate AI-assistant capabilities to accelerate Data Product development and operations
- Set up robust, scalable pipelines leveraging version control and CI/CD frameworks
- Collaborate with international, agile teams to deliver engineering excellence
- Provide actionable technical guidance to team peers to elevate engineering standards
- Drive adoption of Lakehouse architecture principles across Data Product initiatives
Requirements
- 3+ years of experience in Data Engineering with a proven track record of building enterprise-quality Data Products, preferably in Lakehouse architecture
- Proficiency in Python development
- Proficiency in version control systems such as GitHub and CI/CD frameworks such as GitHub Actions
- Strong knowledge of Databricks technologies including PySpark, Delta Lake, and Unity Catalog, or equivalent technology
- Strong knowledge in Agentic AI and frameworks such as LangGraph, MCP, and A2A
- Strong knowledge of industry-standard microservices technologies including Kubernetes and Docker
- Strong English communication skills, both written and spoken, for collaboration with international teams
- Ability to provide actionable technical guidance and implement engineering excellence practices among agile team peers
Benefits
We connect like-minded people:
- Delivering innovative solutions to industry leaders, making a global impact
- Enjoyable working environment, whether it is the vibrant office or the comfort of your own home
- Opportunity to work abroad for up to two months per year
- Relocation opportunities within our offices in 55+ countries
- Corporate and social events
We invest in your growth:
- Leadership development, career advising, soft skills and well-being programs
- Certifications, including GCP, Azure and AWS
- Unlimited access to EPAM's internal learning database