Senior Data Engineer- Data Platform

<h3>Accountabilities</h3><li>Own production data systems and key data domains across the full lifecycle, from ingestion and validation through storage, transformation, and downstream delivery.</li><li>Design robust ingestion patterns capable of handling incomplete, duplicated, delayed, malformed, and evolving data from external and internal sources.</li><li>Define clear data contracts between source systems, ingestion processes, transformations, and downstream consumers.</li><li>Design and maintain reliable data models with well-defined grain, keys, history, and business definitions to ensure consistent and trustworthy results.</li><li>Safely evolve schemas, pipelines, and datasets while supporting retries, backfills, replay, and reprocessing without introducing corruption or duplication.</li><li>Improve pipeline performance, observability, monitoring, and failure handling so issues can be detected, diagnosed, and resolved effectively.</li><li>Partner with Engineering, Product, Operations, and Analytics teams to determine how data should be represented when requirements are incomplete, complex, or evolving.</li><li>Make thoughtful architecture and production decisions that balance reliability, scalability, maintainability, performance, and cost.</li><li>Document technical decisions and communicate data architecture, changes, and tradeoffs clearly to both technical and non-technical stakeholders.</li><h2>Requirements</h2><li>Bachelor’s degree or equivalent educational background.</li><li>5+ years of professional experience building and operating production data systems.</li><li>Strong SQL and data modeling expertise, including experience with grain, keys, historical data, dimensional modeling, and evaluating alternative data representations.</li><li>Demonstrated experience designing and operating batch and asynchronous data pipelines, with a solid understanding of distributed-system failure modes.</li><li>Experience working with cloud-based data platforms, including knowledge of storage, query performance, scalability, and cost considerations.</li><li>Strong understanding of data correctness, including validation, idempotency, late-arriving and duplicate records, schema evolution, backfills, and reprocessing.</li><li>Working proficiency in Python for developing pipelines, services, tooling, and automated tests.</li><li>Ability to make controlled, reversible changes to production systems while protecting downstream consumers.</li><li>Strong analytical and problem-solving skills, with the ability to work effectively through ambiguous or incomplete requirements.</li><li>Clear written and verbal communication skills, including the ability to explain technical decisions and tradeoffs to stakeholders outside engineering.</li><li>Previous healthcare experience is not required, and candidates do not need experience with every technology used within the organization.</li><li>Ability to work from the United States and authorization to work in the U.S. without employer-sponsored visa support.</li><h2>Benefits</h2><li>Annual salary range of<strong>$160,000–$170,000</strong>, depending on experience and qualifications.</li><li>Fully remote opportunity within the United States.</li><li>Opportunity to work on data infrastructure supporting healthcare products, operations, reporting, and analytics.</li><li>Inclusive and diverse work environment that values different perspectives and backgrounds.</li><li>Commitment to reasonable workplace accommodations for qualified individuals with disabilities and disabled veterans.</li><li>Opportunity to contribute to meaningful technology that helps improve healthcare access and outcomes.</li><li>Employees must reside in and work from the United States; international work is not permitted.</li>