#725 Software Engineer (Lake Analytics Platform)

Job Overview The Lake Analytics Platform (LAP) team builds the trusted analytical architecture that lets data move safely from durable storage to business decisions, internal applications, and AI. The team's work spans the lakehouse foundation (storage, table formats, compute), governance and access (RBAC, data masking, policy-driven grants), a shared semantic layer for business definitions, and the internal developer platforms that turn governed data into working products used across the company. What You'll Do • Operate core platform capabilities: Pick up and extend existing platform features — provisioning, deploy pipelines, access control, and service lifecycle management — for the internal tools and applications the team supports, without needing to make net-new architecture decisions. • Maintain integrations: Support and extend integrations between platform services and internal systems — CI/CD, identity and secrets management, internal APIs, and event-driven hooks. • Support governance work in flight: Continue in-progress access control, data classification, and dynamic masking work on the team's Snowflake-based analytical environment, following patterns already established by the team rather than setting new ones. • Keep self-service tooling running: Maintain and incrementally improve automation that keeps access provisioning, pipeline failure handling, and service health self-service for platform users. • Hold up observability and incident response: Use existing telemetry, alerting, and runbooks to diagnose and resolve platform issues; follow established operational patterns rather than redesigning them. • Share on-call coverage: Participate in on-call rotation and triage production incidents across the platform services you support for the duration of the engagement. • Hand off cleanly: Document decisions and open threads clearly enough that returning team members can pick work back up with minimal context loss at the end of the contract. What We're Looking For • Analytical Data Platform Experience: Hands-on experience operating a cloud analytical data platform (Snowflake, Databricks, BigQuery, or similar), including access control, data masking/governance, and compute management. Comfortable operating with elevated privileges and mindful of blast radius. • Container and Deployment Experience: Experience with containerized applications, CI/CD pipeline design (Buildkite, GitHub Actions, or similar), and deployment automation for production services. • Platform and Developer Tooling: Experience building or operating internal platforms, developer tooling, or self-service infrastructure for other engineers. • Integrations: Comfort with REST APIs, OAuth/OIDC, webhook ingestion, secrets management, and identity/SSO patterns in a managed cloud environment. • Backend Fundamentals: Proficiency in Python and SQL for building and maintaining reliable platform services. • Operational Ownership: Comfortable owning alerts and runbooks written by others, and closing the loop on incidents with root cause analysis. • Fast Ramp-Up: Prior experience joining an existing codebase/platform mid-stream as a contractor or new hire and becoming productive quickly with limited onboarding time. • Communication: Strong written communication — this role depends on clear async updates and documentation given the fixed engagement window and handoff requirements.