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
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Design and implement a lakehouse UniForm write layer with dual-format metadata (Delta + Iceberg) readable by all target consumers without conversion
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Establish and validate GCS-to-BigQuery ingestion pipeline patterns for structured operational data types such as sales, delivery, schedule, and performance data
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Implement change-data-capture (CDC) patterns using Kafka for real-time and near-real-time data movement into the lakehouse
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Develop dependency-aware bookkeeping and data lineage tracking patterns for use across all data pipelines
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Ensure all adapter code is modular, version-controlled, and designed for reuse across new data source integrations
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Configure Iceberg external table definitions within Snowflake's Horizon catalog
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Validate zero-copy read access from Snowflake to managed Iceberg / Delta tables without data movement
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Implement and test tenant-scoped access controls compatible with Snowflake Horizon catalog metadata governance
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Implement and certify a Delta Sharing adapter for live, zero-copy data sharing from Delta Lake tables to Databricks consumers
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Configure Delta Sharing endpoint registration and sharing agreement management
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Register Snowflake and Databricks as named connector types in the connector registry
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Implement RBAC, tenant-scoped authorization, and metering hooks compatible with the billing framework for governed data-out flows
Requirements
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3+ years of experience in data engineering or software engineering roles focused on large-scale data platforms
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Expertise in GCP BigQuery, Apache Iceberg, and Delta Lake
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Proficiency in Python and Spark for building and maintaining data pipelines
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Knowledge of data lake architecture, Iceberg UniForm, and Delta Sharing
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Familiarity with Kafka/CDC patterns for real-time data movement
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Background in Snowflake Horizon catalog and Databricks Unity Catalog integrations
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Active, working experience with AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor
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Capability to demonstrate AI tooling use in a technical screening
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English proficiency at B2 level or higher
We offer
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International projects with top brands
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Work with global teams of highly skilled, diverse peers
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Healthcare benefits
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Employee financial programs
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Paid time off and sick leave
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Upskilling, reskilling and certification courses
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Unlimited access to the LinkedIn Learning library and 22,000+ courses
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Global career opportunities
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Volunteer and community involvement opportunities
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EPAM Employee Groups
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Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn
EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.