Lead Data Integration Engineer

About the role

EPAM is seeking a Lead Data Integration Engineer to design and maintain production dbt and Snowflake models that power GTM analytics and AI agents. You will create trusted semantic layers, unify Salesforce and Gong‑style interaction data, and prepare datasets for Snowflake Cortex and Snowflake Intelligence.

Key responsibilities

• Design and maintain production data models in dbt and Snowflake for account health, engagement velocity, and customer intent signals.
• Integrate structured records with unstructured interaction data (call transcripts, emails, CRM objects, telemetry) into reliable account‑level dimensions.
• Implement an enterprise semantic layer to ensure consistent metric calculations across business tools.
• Prepare clean, context‑rich datasets optimized for Snowflake Cortex, Snowflake Intelligence, and internal AI agents.
• Develop automated tests, schema validations, and freshness monitors in dbt for both structured and unstructured data.
• Enforce data governance, RBAC, and audit trails for sensitive sales pipeline data.

Required profile

• 5+ years of commercial experience in analytics engineering, data engineering, or data architecture.
• Expert‑level proficiency in advanced SQL (window functions, CTEs, complex joins, query optimization).
• Extensive hands‑on experience with production dbt projects and Snowflake administration.
• Demonstrated experience modeling B2B SaaS revenue and interaction data (Salesforce, Gong, Marketo, subscription billing).
• Daily comfort with Git workflows, branching strategies, code reviews, and CI testing.

Required skills

• SQL
• dbt
• Snowflake
• Git
• Python (Pandas)
• AI‑assisted development tools (GitHub Copilot, Claude Code)

What we offer

• International projects with top brands
• Healthcare benefits and employee financial programs
• Paid time off, sick leave, and upskilling opportunities
• Unlimited access to LinkedIn Learning library (22,000+ courses)
• Global career opportunities and volunteer programs