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Health Tech, Fintech, SaaS, Data Analytics

Senior Data Engineer

RemoteRemoteFull TimeSenior$140,000–$175,000 /yrPosted 1 month agoVisa sponsorship available

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Required skills

  • data products
  • Medicare
  • Medicaid
  • Commercial data
  • claims
  • eligibility / enrollment data
  • SQL
  • Python
  • data modeling
  • data warehousing

Nice to have

  • dbt
  • data transformation
  • Great Expectations
  • Monte Carlo
  • dbt tests
  • ambiguous environments

Role summary

Accorded is seeking a Senior Data Engineer to build and optimize healthcare data integration and transformation pipelines, ensuring high data integrity. The role involves designing and maintaining complex domain and business logic models for their Acumen product. This position requires close collaboration with internal teams (Actuarial, Product) and direct customer interaction for troubleshooting and issue resolution. Candidates must uphold engineering standards, participate in code reviews, and effectively leverage AI-assisted development. A strong background in data modeling, warehousing, ETL, SQL, Python, and cloud data warehouses (BigQuery, Snowflake, Redshift) is essential, along with 5+ years of data product experience and specific healthcare domain knowledge (Medicare, Medicaid, Commercial data). Experience with AI-supported software development is also required.

Key Responsibilities

  • Healthcare Data Integration: Build, maintain, and optimize healthcare data integrations and transformation pipelines, incorporating robust testing to ensure high data integrity.
  • Product Development: Design, implement, and maintain complex domain and business logic models to continuously advance and prove out Accorded’s Acumen product.
  • Cross-Functional & Client Collaboration: Work closely with internal teams (Actuarial, Product) and interface directly with customers to deliver high-quality data integrations, provide technical troubleshooting, and resolve pipeline issues.
  • Uphold Engineering Standards: Participate in code reviews, maintain rigorous code quality standards, and leverage modern tools including AI-assisted development effectively and responsibly.

Required Qualifications

  • 5+ years of engineering experience working directly with data products.
  • Healthcare Domain Experience: Hands-on experience with Medicare, Medicaid, or Commercial data (payor or provider side), with expertise in healthcare data, preferably claims and eligibility / enrollment data.
  • Core Data Engineering Background: Strong proficiency in SQL and Python, along with extensive experience in data modeling, data warehousing, and ETL processes.
  • Cloud Data Warehousing: Production experience with cloud data warehouses such as BigQuery, Snowflake, or Redshift.
  • Analytics Product & Team Support: Experience working directly with an analytics product and operating or supporting an analytics delivery team.
  • Experience with AI-Supported Software Development: Demonstrated ability to use AI tools for development effectively and responsibly (e.g., knowing when to trust AI outputs and how to rigorously test AI-led code changes).

Preferred Qualifications

  • DBT Experience: Professional experience with dbt (data build tool) for data transformation layers.
  • Data Quality & Observability: Hands-on experience implementing data automated testing and monitoring frameworks (e.g., Great Expectations, Monte Carlo, dbt tests).
  • Early-Stage / Startup Agility: Track record of operating in fast-paced, ambiguous environments with high autonomy and direct product ownership.
  • Customer-Facing Technical Experience: Demonstrated ability to interface directly with external clients/partners for technical integration scoping, data onboarding, and hands-on troubleshooting.

Additional Information

  • Accorded is located in the San Francisco Bay Area. Remote candidates living and authorized to work in the United States are eligible to apply
  • Accorded is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive work environment and do not discriminate on the basis of race, color, religion, gender, gender identity, sexual orientation, national origin, genetics, disability, age, or veteran status.
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