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Accorded is building a product that translates complex healthcare data and analytics into actionable financial and clinical insights. As a Senior Data Engineer, you will directly shape and prove out the core product, Acumen, working closely alongside actuaries, engineers, and product leaders to turn messy healthcare data into scalable, high-performing data models.
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.
• Engineering Standards: Participate in code reviews, maintain rigorous code quality standards, and leverage modern tools including AI-assisted development effectively and responsibly.
The company values high ownership, low bureaucracy, and modern engineering practices. You'll drive architectural decisions and use cutting-edge tools on a highly collaborative team where your work has immediate impact.
REQUIREMENTS:
• 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 (knowing when to trust AI outputs and how to rigorously test AI-led code changes)
PREFERRED QUALIFICATIONS:
• dbt (data build tool) experience for data transformation layers
• Data Quality & Observability: Hands-on experience implementing 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
