Data Platform Engineer

Overview In this role, you will build the data backbone for Hadrian’s autonomous factories, turning machine signals and operational data into trusted datasets for scheduling, ML, and analytics. You’ll own data ingestion, streaming, contracts, quality, and lineage to enable reliable, scalable analysis and AI-driven decision-making. You’ll work with cross-functional teams to integrate diverse data sources from factory floor systems. This is a data-platform and distributed-systems role with high impact on manufacturing outcomes. Compensation / BenefitsMedical, dental, vision, and life insurance401kRelocation support may be providedFlexible vacation policyEquityOn-site employment in Los Angeles ResponsibilitiesBuild the data backbone for factory data used by scheduling, ML, and operationsDevelop ingestion, CDC, and streaming for transactional data, events, telemetry, and files with strong focus on ordering, retries, idempotence, and backpressureDefine versioned data and event contracts with upstream teams and ensure data freshness and correctnessModel telemetry, quality events, work orders, and operational data with clear grain, identity, time, provenance, and historyOwn Dagster orchestration, dbt transformation, data CI/CD, backfills, lineage, observability, and offline feature datasets for MLCollaborate with Manufacturing Operations and Infrastructure to acquire data from machines, PLCs, historians, OPC-UA, MTConnect, and MQTT sources as needed Key requirementsExperience building and operating production data infrastructure or distributed data systems with on-call ownership and recoveryStrong production Python and advanced SQL and data-modeling skills including incremental processing, temporal data, and schema evolutionExperience with Kafka or another event-streaming platform and CDC or stateful incremental pipelinesExperience operating Snowflake and lakehouse formats (Iceberg, Delta, or Hudi) with partitioning and compactionExperience with Dagster, Airflow, Argo, or Prefect; dbt or similar transformation frameworks; and Kubernetes or infrastructure as codeStrong judgment on contracts, failure modes, and needs of downstream analytics, ML, and operational systemsPythonSQLKafka or other event-streaming platformCDC and incremental pipelinesSnowflakelakehouse formats (Iceberg, Delta, or Hudi)