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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Platform Engineer - **Company:** Hadrian Inc. - **Location:** Los Angeles, CA, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Continuous Integration, Data Infrastructure, Distributed Data Store, Python (Programming Language), Message Queuing Telemetry Transport (MQTT), Operational Data Store, Operational Databases, OPC Unified Architecture, Data Streaming, Transaction Data, Data Ingestion, Sql Optimization, Snowflake, Kubernetes, Apache Kafka, Operational Systems - **Published:** August 7, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/data-platform-engineer-los-angeles-ca-usa-58826976 ## About the Role and identity, time, provenance, and history * Own Dagster orchestration, dbt transformation, data CI/CD, backfills, lineage, observability, and offline feature datasets for ML * Collaborate with Manufacturing Operations and Infrastructure to acquire data from machines, PLCs, historians, OPC-UA, MTConnect, and MQTT sources as needed Tasks * Experience building and operating production data infrastructure or distributed data systems with on-call ownership and recovery * Strong production Python and advanced SQL and data-modeling skills including incremental processing, temporal data, and schema evolution * Experience with Kafka or another event-streaming platform and CDC or stateful incremental pipelines * Experience operating Snowflake and lakehouse formats (Iceberg, Delta, or Hudi) with partitioning and compaction * Experience with Dagster, Airflow, Argo, or Prefect; dbt or similar transformation frameworks; and Kubernetes or infrastructure as code * Strong judgment on contracts, failure aaa ## Description Experteer 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 / Benefits * Build the data backbone for factory data used by scheduling, ML, and operations * Develop ingestion, CDC, and streaming for transactional data, events, telemetry, and files with strong focus on ordering, retries, idempotence, and backpressure * Define versioned data and event contracts with upstream teams and ensure data freshness and correctness * Model telemetry, quality events, work orders, and operational data with clear grain, identity, time, provenance, and history * Own Dagster orchestration, dbt transformation, data CI/CD, backfills, lineage, observability, and offline feature datasets for ML * Collaborate with Manufacturing Operations and Infrastructure to acquire data from machines, PLCs, historians, OPC-UA, MTConnect, and MQTT sources as needed Tasks * Experience building and operating production data infrastructure or distributed data systems with on-call ownership and recovery * Strong production Python and advanced SQL and data-modeling skills including incremental processing, temporal data, and schema evolution * Experience with Kafka or another event-streaming platform and CDC or stateful incremental pipelines * Experience operating Snowflake and lakehouse formats (Iceberg, Delta, or Hudi) with partitioning and compaction * Experience with Dagster, Airflow, Argo, or Prefect; dbt or similar transformation frameworks; and Kubernetes or infrastructure as code * Strong judgment on contracts, failure modes, and needs of downstream analytics, ML, and operational systems Key requirements * Medical, dental, vision, and life insurance * 401k * Relocation support may be provided * Flexible vacation policy * Equity * On-site employment in Los Angeles ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)