Описание
Analytics Data Platform Lakehouse team builds and operates the foundations that power data engineers, applied AI, and product teams—managing millions of tables on their behalf and simplifying operations from maintenance and observability to governance, for both internal and customer-facing use cases. If you're excited by the intersection of petabyte data processing scale, open-source query engines, and building platforms with real product stakes, this is the team for you. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table.
We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design, build, and operate core components of our lakehouse platform, including Apache Iceberg table management (data compaction, data layout optimization, materialized view scheduling…) and Iceberg catalog Drive adoption of open table formats across internal teams, owning the integration of Trino, Spark and other query engines (DuckDB, Puppygraph…) with our Iceberg-based at petabyte scale Build observability for managed iceberg tables, to identify query performance bottlenecks, cost drivers and contribute fixes back to upstream open-source projects (Iceberg, Trino, Spark, Open Lineage) where relevant Build self-serve tooling and abstractions that allow data engineering teams to reliably run thousands of pipelines per day against our lakehouse Collaborate with data engineers, analysts, and infrastructure teams to define the roadmap for our lakehouse architecture and shape how Datadog manages analytic data at scale <
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