Senior Data Engineer- Data Platform

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer – Data Platform based in United States. This is a high-impact opportunity to shape and operate the data platform supporting a complex, data-driven healthcare environment. You will own critical data systems and domains end to end, from ingestion and validation through transformation and delivery. The role focuses on building reliable infrastructure that can handle imperfect, high-volume, real-world data from multiple sources. You will make architectural decisions, improve production reliability, and establish strong standards for data quality and modeling. Working closely with Engineering, Product, Operations, and Analytics, you will turn ambiguous data needs into scalable technical solutions. You will also help guide engineering decisions and strengthen the foundations that power reporting, analytics, and core business operations. 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.