Sr. Data Engineer (Claims)

Alaffia Health • New York, NY

2h

About The Position

Alaffia Health is a healthcare AI startup revolutionizing medical billing, analytics, and data Alaffia Health is a healthcare AI startup revolutionizing medical billing and data automation. Our AI-driven platform leverages state-of-the-art generative AI and machine learning technologies to enhance accuracy, efficiency, and compliance in medical billing and auditing. As we scale, we are seeking a Senior Data Engineer to build the cutting-edge AI products, drive innovation, and shape the future of healthcare automation.
At Alaffia Health, we are looking for an experienced data engineer who is passionate about building modern applications and scalable systems. Our platform leverages cutting-edge technologies to revolutionize healthcare claims payment adjudication and audit workflows. We seek someone who thrives on solving complex data challenges, leveraging AI agents at scale while ensuring security considerations are an uncompromisable requirement in all solutions. In this role, you'll be building the future of healthcare automation while tackling challenging problems in data management, system integration, security and cloud infrastructure.

Requirements

• Code Fluency
• Hands on experience leverage AI development tooling (Cursor, Claude Code, etc…)
• Preemptively identify and resolve technical risks before they jeopardize the project. Resolve cross-team dependencies earlier to ensure the successful execution of the project.
• Avoid re-inventing the wheel by leveraging other Alaffia Health solutions or off-the-shelf solutions with the possible trade-off in mind.
• Architecture Design
• Create coherent designs with multiple components interacting across API or system boundaries; bugs do not creep in at the boundaries between components due to mismatches in expectations of what is technically feasible.
• Capable of rolling out a component or major feature (and deprecating an existing system or feature) reliably - including appropriate monitoring, paging, etc are in place, and that failure domains are understood and characterized appropriately, avoid introducing toil and future maintenance work by proactively avoiding scaling issues and providing adequate documentation before large scale rollout. For early stage products, roll out with an eye toward achieving learning goals untainted by poor quality and know when to make appropriate tradeoffs for “failing fast”.
• Design clear success metrics and achieve those metrics consistently post-launch through the lifetime of the system or feature. For early stage products, those success metrics may be oriented around learning goals rather than usage goals, given the inherent unpredictability of achieving product/market fit.
• Business Acumen
• Engage in listening sessions to increase learning to guide work/priorities
• Have a working knowledge of Alaffia Health’s strategy and organization structure to work effectively across the org and able to help other engineers to effectively collaborate
• 5–10+ years in data engineering, with at least 3–5 years handling healthcare data, particularly:
• Payer claims, eligibility/membership, provider files, and remittances (e.g., EDI 837/835).
• Understanding of payer concepts: benefit structures, adjudication logic, denials, and pricing.
• Statistics & Data Analytics: Deep understanding of statistical modeling, data analytics
• Data Engineering: Proficiency in data cleaning, preparation, data schema design, versioning and database management
• Strong SQL and data modeling:
• Expert‑level SQL plus dimensional and data‑vault style modeling for analytics and downstream apps.
• Experience building semantic layers and standardized metrics for claims and cost/utilization reporting.
• Modern data engineering tools:
• Proven work with dbt or similar transformation frameworks, and orchestration tools like Airflow, Dagster, or Prefect for batch/stream pipelines.
• Programming and integration:
• Strong Python for ETL/ELT, APIs, and data quality checks; plus familiarity with REST/JSON, FHIR, and EDI‑style feeds where relevant
• Building SasS applications in the healthcare sector or other highly regulated industries

Nice To Haves

• Machine learning and deep learning concepts.
• Cloud warehouses and lakehouses such as Snowflake, BigQuery, Redshift, or Delta Lake; comfort with performance tuning and cost management.
• Experience with DevOps and cloud providers, such as AWS, Azure, and GCP
• Autonomous learning, self-leadership, and the ability to own system components while collaborating with other SME’s
• Exceptional problem-solving skills and the ability to work in a fast-paced, evolving environment
• Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to non-technical stakeholders

Responsibilities

• Ensure all internal and external reports are delivered on-time and with accuracy, including scheduled client deliverables and internal operational dashboards.
• Work closely with stakeholders to produce detailed reporting requirements, documentation, and SOPs, ensuring clarity on metric definitions and data lineage.
• Execute, maintain, and progressively automate manual reporting tasks, using SQL, scripting, and BI tooling to reduce operational burden.
• Own and enhance report-focused apps in Retool, including building new views, improving UX, and integrating with underlying data sources.
• Partner with data engineering to design and improve ETL/ELT workflows and data models that support scalable, performant reporting.
• Perform data investigations and root-cause analyses when report discrepancies, anomalies, or data quality issues occur, and drive resolution.
• Act as a subject matter expert on healthcare claims reporting, helping internal and external stakeholders interpret trends, metrics, and exceptions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed