Data Engineer

Architect and maintain the certified dataset layer in dbt: models, tests, documentation, and SLAs the whole company trusts.

Build well-modeled, context-rich datasets that power self-service analytics, operations research, and LLM-based data apps at company scale.

Define metric standards: canonical definitions, calculation logic, ownership, refresh cadence.

Implement canonical data models and semantic layer that scale from 1 to 20+ factories.

Partner with Data Platform Engineering to harden the unified data platform and set standards.

Partner with OR Scientists and Data Scientists on feature-set prep and model-output stores.

Evaluate and recommend analytical tooling (BI platforms, notebook environments, metric layers).

Define analytical-engineering standards: naming, testing, CI/CD for the dbt project, documentation.

Mentor the Data Analysts to drive consistency and governance across datasets.

Production ownership of data models (years scale with level; see Level & Justification).

Expert SQL (window functions, CTEs) with a real grasp of query performance and cost.

Ships production data pipelines with Spark, dbt, and Dagster or equivalents.

Strong data-modeling foundation (normalization, denormalization, star/snowflake schemas).

Familiar with lake and warehouse internals (columnar stores, Iceberg catalog, partitioning, materializations).

Builds semantic layers with dbt, Snowflake, or Databricks.

Python for reusable pipeline and data-app utilities.

End-to-end ownership, with a quality bar that doesn't stall progress.

Cross-functional data marts and pipelines.

ClickHouse optimization (materialized views, projections, TTL).

Manufacturing statistics: SPC, control charts, process capability.

Data mesh and data-product concepts.

Orchestration depth (Dagster, Airflow).

Scaling analytics across multiple sites or business units.

Background in Operations Research, industrial engineering, or quantitative finance.

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 candidacy. Candidate data processed through these tools is subject to the same protections described in our Privacy Policy .

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.