Data Engineer III - (Data Platforms) at Cedar

, , United States -

Full Time

Start Date

Immediate

Expiry Date

22 Apr, 26

Salary

215000.0

Posted On

22 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, SQL, Python, ETL, dbt, Airflow, Snowflake, Data Modeling, Cloud Platforms, Collaboration, Communication, Testing Strategies, Data Governance, Metadata, Analytics, Visualization Tools

Industry

Hospitals and Health Care

Description

Our healthcare system is the leading cause of personal bankruptcy in the U.S. Every year, over 50 million Americans suffer adverse financial consequences as a result of seeking care, from lower 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. Cedar’s mission is to leverage data science, smart product design and personalization to make healthcare more affordable and accessible. Today, healthcare providers still engage with its consumers in a “one-size-fits-all” approach; and Cedar is excited to leverage consumer best practices to deliver a superior experience. The Role Cedar’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 evolve our data ecosystem from homegrown ETL scripts to a modern, scalable stack built on tools like dbt, Airflow and Snowflake. You will contribute to the design and implementation of critical data pipelines (e.g., client billing, product analytics, and platform data services), improve data quality and observability, and help implement patterns and standards for how Cedar 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 scalable ELT/ETL pipelines that power core use cases including client billing, financial reporting, product analytics, and data services for downstream teams (Finance, Data Science, Commercial Analytics, Product). Modernize legacy data flows by migrating SQL- and Liquibase-based transformations into dbt, with solid testing, documentation and data contracts. Improve reliability and observability of our data platform by applying best practices in testing, monitoring, alerting and runbook-driven operations for pipelines orchestrated via Airflow (and/or similar tools). Model data for usability and performance in Snowflake and other systems, applying sound data modeling patterns (e.g., dimensional models, entity-centric 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, well-documented, and delivered in the right form and cadence for consumers. Contribute to Cedar’s data platform vision by implementing standards for governance, metadata and access, and by helping pilot tools like OpenMetadata and data quality frameworks within your projects. Participate in code reviews and design discussions, helping to raise the bar on code quality, reliability, and operational excellence across the team. About You 3+ years of hands-on data engineering (or closely related 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: Snowflake (or similar cloud 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/root-cause analysis. Experience with data modeling and schema design for analytics and reporting use cases (e.g., star/snowflake schemas, event or entity-centric designs). Familiarity with cloud platforms, ideally AWS (e.g., S3, IAM, containerized workloads, or related infrastructure supporting data workloads). Strong collaboration and communication skills, with the ability to break down ambiguous business problems into clear technical tasks and work effectively with partners across engineering, product and business teams. Bias to learn and take ownership in a complex, 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, DataHub or similar catalogs, and implementing data contracts or quality 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-centric architectures. Prior experience in healthcare, fintech, or other highly regulated domains, particularly with standards like HL7 or FHIR, or with complex billing/financial data flows. Familiarity with analytics and visualization tools (e.g., Looker, Hex) and enabling self-serve analytics through well-designed semantic layers and models. Experience contributing to team-level standards, patterns, and roadmaps for data engineering or platform teams (even if not as primary owner). Compensation Range and Benefits Salary/Hourly Rate Range*: $170,000 - $215,000 This role is equity eligible This role offers a competitive benefits and wellness package *Subject to location, experience, and education #LI-DS1 #LI-Remote What do we offer to the ideal candidate? A chance to improve the U.S. healthcare system at a high-growth company! Our leading healthcare financial platform is scaling rapidly, helping millions of patients per year Unless stated otherwise, most roles have flexibility to work from home or in the office, depending on what works best for you For exempt employees: Unlimited PTO for vacation, sick and mental health days–we encourage everyone to take at least 20 days of vacation per year to ensure dedicated time to spend with loved ones, explore, rest and recharge 16 weeks paid parental leave with health benefits for all parents, plus flexible re-entry schedules for returning to work Diversity initiatives that encourage Cedarians to bring their whole selves to work, including three employee resource groups: be@cedar (for BIPOC-identifying Cedarians and their allies), Pridecones (for LGBTQIA+ Cedarians and their allies) and Cedar Women+ (for female-identifying Cedarians) Competitive pay, equity (for qualifying roles), and health benefits, including fertility & adoption assistance, that start on the first of the month following your start date (or on your start date if your start date coincides with the first of the month) Cedar matches 100% of your 401(k) contributions, up to 3% of your annual compensation Access to hands-on mentorship, employee and management coaching, and a team discretionary budget for learning and development resources to help you grow both professionally and personally About us Cedar was co-founded by Florian Otto and Arel Lidow in 2016 after a negative medical billing experience inspired them to help improve our healthcare system. With a commitment to solving billing and patient experience issues, Cedar has become a leading healthcare technology company fueled by remarkable growth. "Over the past several years, we've raised more than $350 million in funding & have the active support of Thrive and Andreessen Horowitz (a16z). As of November 2024, Cedar is engaging with 26 million patients annually and is on target to process $3.5 billion in patient payments annually. Cedar partners with more than 55 leading healthcare providers and payers including Highmark Inc., Allegheny Health Network, Novant Health, Allina Health and Providence.

Responsibilities

Design, build, and maintain scalable ELT/ETL pipelines for core use cases such as client billing and product analytics. Collaborate with various teams to ensure data accuracy and improve the reliability of the data platform.