Senior Data Software Engineer

We are seeking a Senior Data Software Engineer to design and implement lakehouse architecture, data-sharing integrations, and governed access layers that power our data platform. The ideal candidate will build scalable, dual-format data pipelines and establish integration patterns across Snowflake and Databricks ecosystems while leveraging AI-assisted development tools throughout the engineering workflow.

Responsibilities

• Design and implement a lakehouse UniForm write layer with dual-format metadata (Delta + Iceberg) readable by all target consumers without conversion
• Establish and validate GCS-to-BigQuery ingestion pipeline patterns for structured operational data types such as sales, delivery, schedule, and performance data
• Implement change-data-capture (CDC) patterns using Kafka for real-time and near-real-time data movement into the lakehouse
• Develop dependency-aware bookkeeping and data lineage tracking patterns for use across all data pipelines
• Ensure all adapter code is modular, version-controlled, and designed for reuse across new data source integrations
• Configure Iceberg external table definitions within Snowflake's Horizon catalog
• Validate zero-copy read access from Snowflake to managed Iceberg / Delta tables without data movement
• Implement and test tenant-scoped access controls compatible with Snowflake Horizon catalog metadata governance
• Implement and certify a Delta Sharing adapter for live, zero-copy data sharing from Delta Lake tables to Databricks consumers
• Configure Delta Sharing endpoint registration and sharing agreement management
• Register Snowflake and Databricks as named connector types in the connector registry
• Implement RBAC, tenant-scoped authorization, and metering hooks compatible with the billing framework for governed data-out flows

Requirements

• 3+ years of experience in data engineering or software engineering roles focused on large-scale data platforms
• Expertise in GCP BigQuery, Apache Iceberg, and Delta Lake
• Proficiency in Python and Spark for building and maintaining data pipelines
• Knowledge of data lake architecture, Iceberg UniForm, and Delta Sharing
• Familiarity with Kafka/CDC patterns for real-time data movement
• Background in Snowflake Horizon catalog and Databricks Unity Catalog integrations
• Active, working experience with AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor
• Capability to demonstrate AI tooling use in a technical screening
• English proficiency at B2 level or higher

Benefits

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn