Senior Data Architect: End-to-End Data Product Leader

Trinity Partners, LLC; United States; On-site; USD 156,000 - 234,000; Full time

Job summary

Trinity Life Sciences seeks an experienced Senior Data Architect to own data product architecture end to end, translating business needs into scalable data pipelines. You will drive normalization of unstructured text, entity resolution, and provenance while collaborating with data scientists and AI engineers.

The role combines hands‑on design and build work with opportunities to extend into AI‑assisted full stack development, interface tools for analysts, and production‑scale data workflows.

Qualifications

• 8+ years of hands‑on data engineering and data architecture experience.
• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
• Depth in data modeling, grain, keys, entity resolution, provenance, and schema evolution.
• Strong SQL and data warehouse expertise; performance optimization.
• Strong Python for production data pipelines with orchestration and observability.

Responsibilities

• Own the data product architecture end‑to‑end for Trinity data products.
• Design and build normalization pipelines for heterogeneous text sources.
• Create multi‑stage pipelines with deterministic parsing, AI-assisted extraction, and human review.
• Collaborate with domain experts, data scientists, and AI engineers to translate requirements into architecture.
• Optional: develop internal interfaces for pipeline review and modification.

Skills

Data architecture

Data engineering

SQL

Python

Entity resolution

Unstructured data

Cloud platforms

Communication

Education

Bachelor’s degree in Computer Science or related field

Tools

Git

Jenkins

CodePipeline

PySpark

Job description

Trinity Life Sciences seeks an experienced Senior Data Architect to own data product architecture end to end, translating business needs into scalable data pipelines. You will drive normalization of unstructured text, entity resolution, and provenance while collaborating with data scientists and AI engineers.

The role combines hands‑on design and build work with opportunities to extend into AI‑assisted full stack development, interface tools for analysts, and production‑scale data workflows.