Lead Data & AI Engineer — Hybrid UK & Enterprise ML

EPAM Systems, Inc.; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

EPAM Employee Stock Purchase Plan (ES

Private medical insurance

Dental care

Employee Assistance Program

Job summary

EPAM Systems, Inc. is seeking a Lead Data & AI Engineer in the UK to design and deliver advanced data solutions on cloud platforms. You'll build scalable data pipelines, ensure data quality, and enable AI feature engineering for analytics and intelligent applications.

Role requires hands-on expertise in data engineering, AI integration, governance, and enterprise-scale security. Hybrid UK model with multi-cloud readiness and strong collaboration with data scientists.

Qualifications

• Minimum 8+ years in data engineering with leadership experience.
• Strong SQL performance tuning for large-scale systems.
• Python programming in data engineering workflows.
• Distributed processing with PySpark.
• Azure Data Factory orchestration and Databricks usage.
• Experience in AI/ML integration and MLOps workflows.
• CI/CD for data and ML pipelines (GitHub Actions, Azure DevOps).
• GenAI-enabled development workflows and data governance.

Responsibilities

• Design robust data architectures on cloud platforms.
• Build large-scale ETL/ELT pipelines for heterogeneous data.
• Create data models for AI/ML pipelines and analytics.
• Develop streaming and batch pipelines with Databricks.
• Operationalize ML solutions with feature stores and registries.
• Collaborate with data scientists to deploy models and monitor them.
• Integrate GenAI into data workflows for automation.
• Ensure data governance, lineage, cataloging, and quality.

Skills

SQL Tuning

Python

PySpark

Delta Lake

Azure Data Factory

GenAI

MLOps

CI/CD

GitHub Actions

Tools

Databricks

dbt

Job description

EPAM Systems, Inc. is seeking a Lead Data & AI Engineer in the UK to design and deliver advanced data solutions on cloud platforms. You'll build scalable data pipelines, ensure data quality, and enable AI feature engineering for analytics and intelligent applications.

Role requires hands-on expertise in data engineering, AI integration, governance, and enterprise-scale security. Hybrid UK model with multi-cloud readiness and strong collaboration with data scientists.