Data Platform Engineer

Multicoin; Los Angeles (CA); On-site; USD 170,000 - 300,000; Full time

Benefits offered by this job

Medical, dental, vision, and life 보험

401k

Relocation support

Flexible vacation

Equity

Job summary

Hadrian in the United States is seeking a Data Platform Engineer to own the data flow from source to trusted datasets, enabling analytics, data science, and manufacturing operations across autonomous facilities.

You will build ingestion, CDC, streaming, lakehouse storage, and orchestration, ensuring data quality and lineage. Collaboration with Operations and Infrastructure to integrate machines and industrial protocols is essential.

Qualifications

• Experience building and operating production data infrastructure or distributed data systems.
• 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, plus CDC or other stateful incremental pipelines.
• Experience operating Snowflake, and with a lakehouse table format such as Iceberg, Delta, or Hudi, including expertise in partitioning and compaction.
• Experience with Dagster, Airflow, Argo, or Prefect; dbt or similar transformation frameworks; and Kubernetes or infrastructure as code.
• Strong judgment regarding contracts, failure modes, and the needs of downstream analytics, ML, and operational systems.

Responsibilities

• Build the data backbone for autonomous factories, transforming machine signals, quality events, work orders, and application changes into trusted data used by scheduling, ML, and operations.
• Build ingestion, CDC, and streaming capabilities for transactional data, events, telemetry, and files; explicitly manage ordering, deletes, retries, replay, idempotence, and backpressure.
• Define versioned data and event contracts with upstream teams, supported by testing and service targets for freshness, completeness, and correctness.
• Model telemetry, quality events, work orders, and operational data into datasets with explicit 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.

Skills

Python

SQL

Data modeling

Kafka

Snowflake

Dagster

Airflow

Argo

Prefect

dbt

Kubernetes

Go/Rust/Scala

Contract design

Tools

Dagster

Airflow

Argo

Prefect

dbt

Kubernetes

Job description

Hadrian - Manufacturing the Future

Hadrian is building autonomous factories to reindustrialize America. By combining AI, advanced software, robotics, and full-stack manufacturing, we help aerospace and defense companies build rockets, satellites, aircraft, ships, and other mission-critical systems up to 10x faster and at significantly lower cost.

Following our $1.37B Series D at a $7.87B valuation, Hadrian is rapidly expanding our manufacturing footprint, launching new capabilities across welding, casting, forging, electronics, additive manufacturing, and more, while scaling our Factory-as-a-Service platform to transform how critical products are built.

Backed by leading investors including JPMorgan Chase, Valor Equity Partners, Andreessen Horowitz, Founders Fund, 137 Ventures, Lux Capital, T. Rowe Price, and Morgan Stanley, we’re building the future of American manufacturing—and looking for exceptional people to help make it happen.

If you’re ready to take on the most challenging and rewarding work of your career while helping create American manufacturing jobs for generations to come, you’re exactly who we’re looking for.

The Role

Hadrian's factory data originates from production applications, operational databases, quality systems, ERP systems, and machines on the factory floor. This data fuels production schedules, machine-learning systems, engineering analysis, and company reporting.

As a Data Platform Engineer, you will own key segments of the data flow from source to trusted dataset: ingestion, change data capture, streaming, lakehouse storage, orchestration, transformation, contracts, quality, and lineage. Some data sources may involve machines, PLCs, historians, and industrial protocols. Controls experience is advantageous but not required.

This is a data-platform and distributed-systems role. Your work should enable new sources to be integrated easily, make failures straightforward to repair, and ensure datasets are reliable for use by Analytics, Data Science, Operations Research, and ML systems.

What You'll Do

• Build the data backbone for autonomous factories, transforming machine signals, quality events, work orders, and application changes into trusted data used by scheduling, ML, and operations.
• Build ingestion, CDC, and streaming capabilities for transactional data, events, telemetry, and files; explicitly manage ordering, deletes, retries, replay, idempotence, and backpressure.
• Define versioned data and event contracts with upstream teams, supported by testing and service targets for freshness, completeness, and correctness.
• Model telemetry, quality events, work orders, and operational data into datasets with explicit 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.

What We're Looking For

• Experience building and operating production data infrastructure or distributed data systems, including on-call ownership and recovery efforts.
• 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, plus CDC or other stateful incremental pipelines.
• Experience operating Snowflake, and with a lakehouse table format such as Iceberg, Delta, or Hudi, including expertise in partitioning and compaction.
• Experience with tools such as Dagster, Airflow, Argo, or Prefect; dbt or similar transformation frameworks; and Kubernetes or infrastructure as code.
• Strong judgment regarding contracts, failure modes, and the needs of downstream analytics, ML, and operational systems.

What Will Set You Apart

• Experience running Snowflake and Iceberg together or designing a hybrid warehouse and lakehouse architecture.
• Production experience with PeerDB, Debezium, Flink, Spark Structured Streaming, Redpanda, Bufstream, or similar CDC and streaming systems.
• Proficiency with ClickHouse or another low-latency analytical database, including performance tuning and lifecycle management.
• Experience with industrial or edge data collection using OPC-UA, MTConnect, MQTT, historians, PLCs, or handling intermittently connected systems.
• Background in performance-sensitive data systems built with Go, Rust, or Scala; regulated-environment experience; or contributions to dbt, Dagster, Iceberg, or related projects.

Compensation

$170,000 - $300,000

This represents the lowest to highest salary we reasonably and in good faith expect to pay for this role at the time of posting. Actual compensation may fall within or outside this range and the range may be updated in the future. An employee's position within the range will be determined by several factors, including relevant education, qualifications, certifications, experience, skills, geographic location, performance, and organizational needs.

Benefits For Full-time Employees

• Medical, dental, vision, and life insurance plans for employees
• 401k
• Relocation support may be provided for certain situations, based on business need.
• Flexible vacation policy
• Equity

ITAR Requirements

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.

Use of AI in hiring

Hadrian uses AI-assisted tools in our recruiting and hiring processes to help our team work more efficiently. This may include tools that help organize and analyze recruiting data, as well as an AI-powered notetaker that can record and transcribe interviews and help coordinate feedback. These tools support our team and are not used to make hiring decisions. All candidate evaluations and hiring decisions are performed by humans. If an interview will be recorded, you will be notified in advance and may opt out at any time with no impact on your candidity. Candidate data processed through these tools is subject to the same protections described in our Privacy Policy.

Hadrian Is An Equal Opportunity Employer

It is the Company’s policy to provide equal employment opportunity for all applicants and employees. The Company does not unlawfully discriminate on the basis of race inclusive of traits historically associated with race (including, but not limited to, hair texture and protective hairstyles, such as braids, locks and twists), color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, transgender status, national origin (including, in California, possession of a drivers license), ancestry, citizenship, age, physical or mental disability, height or weight, medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, exercise of reproductive rights, any other basis protected by local, state, or federal laws, or any combination of the above characteristics. When necessary, the Company also makes reasonable accommodations for disabled candidates and employees, including for candidates or employees who are disabled by pregnancy, childbirth, or related medical conditions.