Data Platform Engineer III

•    Build and operate batch and streaming ingestion pipelines on Databricks (PySpark, Lakeflow/Delta Live Tables).

•    Integrate event streams from Confluent Kafka into the Lakehouse and manage schema evolution.

•    Build and operate Lakebase-backed operational data patterns alongside the lakehouse.

•    Build ingestion and parsing pipelines for structured and unstructured content (documents, text) feeding the lakehouse, graph and vector stores.

•    Operate and maintain Neo4j environments under established runbooks: backups and restores, monitoring, health checks and routine upgrades.

•    Support vector index operations in Databricks Vector Search and Azure AI Search: run index refresh and sync pipelines and monitor retrieval data freshness.

•    Execute disaster recovery procedures for platform data stores: backup/restore testing, failover drills and multi-region runbook execution.

•    Implement lineage capture and freshness monitoring against published data contracts and SLAs.

•    Automate data-quality and contract testing in CI/CD so violations fail fast, and respond to pipeline incidents.

•    Maintain catalog and metadata hygiene in Unity Catalog, and contribute runbooks and operational documentation for the pipelines you own.