Senior Data Engineer- Data Platform

Accountabilities

Own production data systems and key data domains across the full lifecycle, from ingestion and validation through storage, transformation, and downstream delivery.
Design robust ingestion patterns capable of handling incomplete, duplicated, delayed, malformed, and evolving data from external and internal sources.
Define clear data contracts between source systems, ingestion processes, transformations, and downstream consumers.
Design and maintain reliable data models with well-defined grain, keys, history, and business definitions to ensure consistent and trustworthy results.
Safely evolve schemas, pipelines, and datasets while supporting retries, backfills, replay, and reprocessing without introducing corruption or duplication.
Improve pipeline performance, observability, monitoring, and failure handling so issues can be detected, diagnosed, and resolved effectively.
Partner with Engineering, Product, Operations, and Analytics teams to determine how data should be represented when requirements are incomplete, complex, or evolving.
Make thoughtful architecture and production decisions that balance reliability, scalability, maintainability, performance, and cost.
Document technical decisions and communicate data architecture, changes, and tradeoffs clearly to both technical and non-technical stakeholders.
Requirements
Bachelor’s degree or equivalent educational background.
5+ years of professional experience building and operating production data systems.
Strong SQL and data modeling expertise, including experience with grain, keys, historical data, dimensional modeling, and evaluating alternative data representations.
Demonstrated experience designing and operating batch and asynchronous data pipelines, with a solid understanding of distributed-system failure modes.
Experience working with cloud-based data platforms, including knowledge of storage, query performance, scalability, and cost considerations.
Strong understanding of data correctness, including validation, idempotency, late-arriving and duplicate records, schema evolution, backfills, and reprocessing.
Working proficiency in Python for developing pipelines, services, tooling, and automated tests.
Ability to make controlled, reversible changes to production systems while protecting downstream consumers.
Strong analytical and problem-solving skills, with the ability to work effectively through ambiguous or incomplete requirements.
Clear written and verbal communication skills, including the ability to explain technical decisions and tradeoffs to stakeholders outside engineering.
Previous healthcare experience is not required, and candidates do not need experience with every technology used within the organization.
Ability to work from the United States and authorization to work in the U.S. without employer-sponsored visa support.
Benefits
Annual salary range of $160,000–$170,000, depending on experience and qualifications.
Fully remote opportunity within the United States.
Opportunity to work on data infrastructure supporting healthcare products, operations, reporting, and analytics.
Inclusive and diverse work environment that values different perspectives and backgrounds.
Commitment to reasonable workplace accommodations for qualified individuals with disabilities and disabled veterans.
Opportunity to contribute to meaningful technology that helps improve healthcare access and outcomes.
Employees must reside in and work from the United States; international work is not permitted.