Senior Data Engineer

Medisolv•Clarksville, TN

About The Position

Medisolv is seeking a Senior Data Engineer to provide hands-on technical leadership for its healthcare data platform and customer implementations. The role designs, builds, and operates reliable data products that transform payer and quality data into trusted measure calculations, forecasts, and decision-ready insights. It is a senior individual-contributor position with broad ownership across Snowflake, dbt, orchestration, cloud infrastructure, CI/CD, data quality, and production operations. The engineer partners with product, domain experts, application engineers, security, and client-facing teams, and helps establish scalable engineering patterns and sound technical decisions. The role includes ownership of scalable Snowflake and dbt models; complex data ingestion and connectors; orchestration and production-support patterns; cloud modernization across AWS and Azure; CI/CD and release practices; and technical designs for healthcare quality requirements. It also involves investigating platform and data issues, mentoring through reviews and documentation, and coordinating cross-functional work to meet customer commitments. During the first 30 days, the engineer will build knowledge of the Lilac platform, healthcare-quality domain, data layers, orchestration, cloud environments, release processes, and customer commitments; map critical data flows; review architecture and operational risks; and shadow production support. By 60 days, the engineer is expected to own a platform or integration workstream and deliver or advance a production-ready enhancement. By 90 days, the engineer is expected to lead a cross-functional delivery through production validation and begin prioritized platform improvements.

Requirements

Substantial professional experience building and operating production data platforms, with senior-level ownership of architecture, delivery, and operational outcomes.
Advanced SQL and data-modeling expertise, including production experience with Snowflake and dbt or closely comparable modern cloud-warehouse tooling.
Experience designing robust batch data pipelines and ingestion frameworks, including schema mapping, incremental processing, testing, reconciliation, and failure recovery.
Strong software engineering skills in Python or another production language, with disciplined version control, code review, automated testing, and documentation practices.
Hands-on experience with infrastructure as code and CI/CD, including Terraform and GitHub Actions or comparable tools.
Experience operating across AWS and/or Azure, with practical knowledge of networking, identity, secrets, object storage, monitoring, and secure environment design.
Demonstrated ability to lead complex technical work across engineering, product, domain, security, and client-facing stakeholders.
Commitment to secure handling of regulated healthcare data, least-privilege access, auditability, and production reliability.
Bachelor's degree in computer science, engineering, information systems, data science, or a related discipline, or equivalent practical experience.
Clear written and verbal communication, sound judgment under operational pressure, and the ability to make complex technical tradeoffs understandable.
Must successfully pass a pre-employment background check and be legally authorized to work in the United States; sponsorship is not available.

Nice To Haves

Healthcare payer data experience, especially Medicare Advantage, CMS Star Ratings, HEDIS, CAHPS, HOS, PQA, claims, enrollment, eligibility, pharmacy, or quality-measure calculations.
Experience with Apache Airflow or comparable orchestration, targeted reruns, backfills, data-quality monitoring, and production incident response.
Experience migrating data platforms or containerized workloads from AWS to Azure, including Azure App Service, Key Vault, Blob Storage, Private Link, or Azure DevOps Pipelines.
Experience with forecasting, What-If/scenario modeling, financial or reward calculations, semantic models, or customer-specific analytics products.
Experience with Go/Golang, OIDC/SAML/RBAC, Cognito or enterprise identity integrations, Sigma, or Snowflake-native analytics capabilities.
Professional certifications in Snowflake, dbt, AWS, Azure, or Terraform.

Responsibilities

Own the design and evolution of scalable Snowflake and dbt data models for healthcare quality measurement, forecasting, reporting, and customer-specific workflows.
Lead complex ingestion and connector implementations for claims, enrollment, eligibility, pharmacy, survey, plan, and reference data delivered through SFTP, object storage, data shares, and APIs.
Set engineering patterns for orchestration, incremental processing, dependency management, reruns, reconciliation, and production support across Airflow and related workflows.
Drive cloud modernization across AWS and Azure, including Terraform-based infrastructure, secure connectivity, secrets management, environment promotion, and operational readiness.
Strengthen CI/CD and release practices with automated tests, security checks, observability, and controlled production deployment.
Translate healthcare quality requirements into maintainable technical designs, partnering with domain experts on CMS Star Ratings, HEDIS, CAHPS, HOS, PQA, measure calculations, and scenario modeling.
Investigate complex data and platform issues, lead root-cause analysis, and implement improvements to reliability, performance, cost, and data trust.
Provide technical mentorship through architecture reviews, pull-request feedback, documentation, and reusable patterns, without direct people-management responsibility.
Collaborate with product, client delivery, security, and engineering leaders to scope work, identify dependencies, communicate tradeoffs, and deliver on customer commitments.
Build knowledge of the platform and domain, map data flows, review architecture and operational risks, and participate in production-support shadowing.
Assume technical ownership of a data-platform or customer-integration workstream and deliver or advance production-ready enhancements.
Lead cross-functional delivery from requirements through production validation, including dependency management, data reconciliation, release coordination, and post-release monitoring.