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