Senior Data Engineer

Medisolv, Inc.

. Design and evolve scalable Snowflake and dbt data models supporting healthcare quality measurement, forecasting, reporting, and customer-specific workflows .

Posted 11/3/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating production data platforms with a focus on Snowflake and dbt, advanced SQL, and cloud environments like AWS and Azure. Capable of leading complex technical projects while ensuring secure handling of healthcare data and effective collaboration across cross-functional teams.

Highest-signal resume keywords

Snowflake Data ModelingAdvanced SQL ExpertiseCI/CD with GitHub ActionsInfrastructure as Code with TerraformHealthcare Quality Measurement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingBatch Data PipelinesIncremental ProcessingPython ProgrammingSchema MappingAutomated TestingProduction ReliabilityRoot-Cause AnalysisData Trust ImprovementTechnical Mentorship

Soft Skills

Clear CommunicationSound JudgmentCollaborationProblem-SolvingTechnical Leadership

Tools & Technologies

SnowflakeDbtApache AirflowAWSAzureTerraformGitHub ActionsSFTPAPIsObject Storage

Certifications & Qualifications

Snowflake CertificationDbt CertificationAWS CertificationAzure CertificationTerraform Certification

Industry Keywords

Healthcare Quality MeasurementCMS Star RatingsHEDISCAHPSPQAData GovernanceRegulated Healthcare DataForecastingScenario ModelingData Platform Ownership

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCloudPythonSnowflakeSQLTerraformGo

About the role

Key responsibilities & impact

Design and evolve scalable Snowflake and dbt data models supporting 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
Establish 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 using GitHub Actions and related tooling, with automated tests, security checks, observability, and controlled production deployment
Translate healthcare quality requirements into maintainable technical designs for CMS Star Ratings, HEDIS, CAHPS, HOS, PQA, measure calculations, and scenario modeling
Investigate complex data and platform issues, lead root-cause analysis, and improve 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, surface dependencies, communicate tradeoffs, and deliver customer commitments
Build knowledge of the Lilac platform, healthcare-quality domain, data layers, orchestration, cloud environments, release processes, and customer commitments
Map critical data flows from ingestion through measure calculation, forecasting, reporting, and application consumption
Assume technical ownership of data-platform or customer-integration workstreams and lead cross-functional delivery through production validation and post-release monitoring

Requirements

What you’ll need

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 hands-on 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
Must successfully pass a pre-employment background check
Must be legally authorized to work in the United States
Sponsorship is not available
Strongly preferred: healthcare payer data experience, Apache Airflow or comparable orchestration, AWS-to-Azure migration experience, forecasting or scenario modeling, and experience with Go/Golang, OIDC/SAML/RBAC, Cognito, Sigma, or Snowflake-native analytics
Professional certifications in Snowflake, dbt, AWS, Azure, or Terraform are helpful but not required
Clear written and verbal communication, sound judgment under operational pressure, and ability to explain complex technical tradeoffs

Benefits

Comp & perks

Diverse and inclusive workplace
Pre-employment background check required
U.S.-based/onshore role supporting work with regulated and PHI-sensitive healthcare data