Senior Data Engineer — Remote Data Platform Lead

Openkrill; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

Vida is seeking a Senior Data Engineer to shape a data platform supporting healthcare data across plans, employers, clinical programs, and internal systems. You will own data systems end-to-end—from ingestion and validation to storage, transformation, and delivery—and guide architecture decisions to ensure robust, scalable pipelines.

You will work with cross-functional teams to model data with clear grain, keys, and history, while implementing safe, reversible production changes and strong data

Qualifications

• Bachelor's degree at a minimum.
• 5+ years building production data systems.
• Strong SQL and data modeling fundamentals.
• Experience designing and operating batch and asynchronous data pipelines.
• Experience with a cloud data platform.
• Strong instincts around data correctness and reprocessing.
• Proficiency in Python for pipelines and tooling.
• Ability to implement safe, reversible production changes.

Responsibilities

• Own production data systems end-to-end from ingestion to delivery.
• Design ingestion patterns for incomplete, duplicated, or delayed data.
• Define contracts between source systems, ingestion, and downstream consumers.
• Develop data models with clear grain, keys, history, and consistency.
• Evolve schemas and pipelines with backfills and replay without data corruption.
• Improve pipeline performance, observability, and failure handling.
• Collaborate with Engineering, Product, Operations, and Analytics to represent data needs.

Skills

Years of data systems experience

SQL proficiency

Data modeling fundamentals

Batch & asynchronous pipelines

Cloud data platforms

Data correctness & quality

Python for pipelines

Education

Bachelor's degree

Job description

Vida is seeking a Senior Data Engineer to shape a data platform supporting healthcare data across plans, employers, clinical programs, and internal systems. You will own data systems end-to-end—from ingestion and validation to storage, transformation, and delivery—and guide architecture decisions to ensure robust, scalable pipelines.

You will work with cross-functional teams to model data with clear grain, keys, and history, while implementing safe, reversible production changes and strong data