Senior Data Science Engineer

We are seeking a Senior Data Science Engineer to design and deliver reusable data-sharing adapters and governed access patterns across a cloud analytics lakehouse. You will build reliable integrations, apply strong engineering practices, and help teams consume data safely and efficiently. Responsibilities Design a dual-format lakehouse write layer that supports Delta and Iceberg metadata over one physical dataset Build and validate ingestion patterns from object storage to an analytical warehouse for structured operational data Implement change-data-capture patterns with Kafka for real-time and near-real-time data movement Develop dependency-aware bookkeeping and data lineage tracking patterns across pipelines Ensure adapter code is modular, version-controlled, and reusable for new data source integrations Configure external table definitions to enable governed access for downstream platforms Validate zero-copy read access to Iceberg and Delta tables without unnecessary data movement Implement and test tenant-scoped access controls aligned with metadata governance needs Deliver a Delta Sharing adapter to provide live, zero-copy sharing to external consumers Configure sharing endpoint registration and manage sharing agreements for data products Test end-to-end data freshness and sharing latency against agreed SLA targets Register connector types in a connector registry and enable controlled data-out connectivity Implement RBAC and tenant-scoped authorization for all external data-out paths with auditability Add metering hooks compatible with billing for governed data-out flows Document integration patterns and operating procedures for reuse and support Requirements 3+ years of data science or ML engineering experience using Python, pandas, and scikit-learn Experience building RAG applications, including embeddings and retrieval strategies Strong leadership skills to drive technical decisions and mentor peers across workstreams Proven project ownership skills delivering reusable adapters and integration patterns end to end Advanced software engineering skills in modular design, testing, debugging, and Git workflows Strong SQL skills for analytical querying, validation, and pipeline support Solid cloud fundamentals across AWS, GCP, or Azure, including scalability and latency tradeoffs Hands-on monitoring skills for drift and performance, plus experiment tracking practices Strong AI tooling skills with AI-assisted development tools such as Claude Code, Cursor, or GitHub Copilot Upper-Intermediate English proficiency (B2) for clear technical communication with global stakeholders Nice to have Google Cloud Platform experience with BigQuery and GCS Large Language Models (LLM) fundamentals, including tokenization and context windows Vector database experience for embeddings storage and retrieval LangChain or similar agent framework experience for tool use and orchestration LLM API integration experience, including streaming, rate limits, and cost management We offer 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 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.