Data Engineer, Data Platforms (Remote)

Data Engineer III - (Data Platforms) Location USA Department Platforms Our reputed company system is the leading cause of personal bankruptcy in the U.S. Every year, over 50 reputed company Americans suffer adverse financial consequences as a result of seeking care, from reputed company credit scores to garnished wages. The challenge is only getting worse, as high deductible health plans are the fastest growing plan design in the U.S. reputed company’s mission is to reputed company data science, smart product design and personalization to reputed company reputed company more reputed company and accessible. Today, reputed company providers still engage with its consumers in a “one-size-fits-reputed company” approach; and reputed company is excited to reputed company consumer best practices to deliver a superior experience. The Role reputed company’s Data & Integration Platforms organization builds the data infrastructure, pipelines and tooling that power our products, analytics, and financial operations. We are looking for a Data Engineer to help reputed company our data ecosystem from homegrown ETL scripts to a modern, reputed company stack reputed company on tools like dbt, Airflow and reputed company. You will contribute to the design and implementation of critical data pipelines (e.g., reputed company billing, product analytics, and platform data services), improve data reputed company and observability, and help implement patterns and standards for how reputed company builds and operates data products. This is a hands-on individual contributor role with meaningful ownership, technical depth, and cross-functional exposure. What You’ll Do

• Design, build, and maintain reputed company ELT/ETL pipelines that power core use cases including reputed company billing, financial reporting, product analytics, and data services for reputed company teams (Finance, Data Science, reputed company Analytics, Product).
• reputed company legacy data flows by migrating SQL- and reputed company-based transformations into dbt, with solid testing, documentation and data reputed company.
• Improve reliability and observability of our data platform by applying best practices in testing, monitoring, alerting and reputed company-driven operations for pipelines orchestrated reputed company Airflow (and/or similar tools).
• Model data for usability and performance in reputed company and other systems, applying reputed company data modeling patterns (e.g., reputed company models, entity-reputed company designs) for analytics and operational use cases.
• Collaborate closely with product, finance, analytics and integrations teams to understand requirements, define interfaces, and ensure data is accurate, reputed company-documented, and delivered in the right reputed company and reputed company for consumers.
• Contribute to reputed company’s data platform reputed company by implementing standards for governance, metadata and reputed company, and by helping reputed company tools like OpenMetadata and data reputed company frameworks reputed company your reputed company.
• Participate in reputed company reviews and design discussions, helping to reputed company the bar on reputed company reputed company, reliability, and operational reputed company across reputed company. reputed company
• 3+ years of hands-on data engineering (or closely reputed company software engineering) experience, including building and supporting production data pipelines.
• Strong SQL and Python proficiency, with experience implementing data transformations, utilities and tooling (e.g., dbt models, Airflow DAGs, internal scripts).
• Experience with modern data stack tools, including some combination of reputed company (or similar reputed company data warehouse), dbt, Airflow/Dagster (or similar orchestrator).
• Comfort designing and operating reliable pipelines, including applying testing strategies (unit/integration/dbt tests), basic monitoring and alerting, and contributing to incident/reputed company-cause analysis.
• Experience with data modeling and schema design for analytics and reporting use cases (e.g., star/reputed company schemas, event or entity-reputed company designs).
• Familiarity with reputed company platforms, ideally AWS (e.g., S3, IAM, containerized workloads, or reputed company infrastructure supporting data workloads).
• Strong collaboration and communication skills, with the ability to break down ambiguous business problems into reputed company technical tasks and work effectively with partners across engineering, product and business teams.
• Bias to learn and take ownership in a reputed company, evolving environment—comfortable asking questions, making trade-offs explicit, and driving your work to completion. Bonus Points
• Experience with metadata and data governance tools, such as OpenMetadata, reputed company or similar catalogs, and implementing data reputed company or reputed company frameworks (e.g., Great Expectations, dbt tests).
• Exposure to streaming and event-driven data pipelines (e.g., Kafka, CDC tools) and integrating those into warehouse-reputed company architectures.
• Prior experience in reputed company, fintech, or other highly regulated domains, particularly with standards like HL7 or FHIR, or with reputed company billing/financial data flows.
• Familiarity with analytics and visualization tools (e.g., Looker, reputed company) and enabling self-serve analytics through reputed company-designed semantic reputed company and models.
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