Senior Data Engineer, Platform

Vanna Health

. Own the infrastructure and platform supporting data jobs, including compute choices, orchestration, deployment, connectivity, reliability, and observability .

Posted 11/3/2026full-timeRemote • United StatesSenior💰 $180,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data infrastructure and platform management, including ownership of AWS and Databricks architecture, while ensuring reliability, observability, and compliance with healthcare regulations. Proficient in building and optimizing data pipelines, mentoring engineers, and leading technical direction in data engineering.

Highest-signal resume keywords

AWS Platform ArchitectureDatabricks ExperienceDistributed Data ProcessingPython ProgrammingCI/CD and Infrastructure as Code

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLDatabricksSparkTerraformGitLab CI/CDAutomated TestingData Pipeline DesignObservabilityIncident Response

Soft Skills

MentoringTechnical LeadershipCommunication

Tools & Technologies

AWSS3FHIRHL7Delta LakeUnity CatalogDbtGenieMCP Servers

Industry Keywords

HealthcareRegulated DataHIPAASOC 2ClaimsEligibility

Tech Stack

Tools & technologies

AWSBigQueryCloudPythonRaySnowflakeSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Own the infrastructure and platform supporting data jobs, including compute choices, orchestration, deployment, connectivity, reliability, and observability
Set technical direction, make architecture decisions, write design documentation, and make build-versus-buy decisions
Shape the data platform roadmap, own delivery, and communicate progress, risks, and trade-offs
Establish design and code-review standards, mentor engineers, and unblock platform contributors
Own Databricks and AWS platform architecture, including ingestion, storage, compute, access control, and environments
Build tested, versioned connections to payer claims, eligibility, attribution, clinical, event, and care-platform systems over SFTP, S3, private networking, FHIR, and HL7
Optimize job performance and cost through compute selection, right-sizing, serverless or cluster decisions, and migration from single-machine Python to distributed compute
Own orchestration, deployments, Terraform, GitLab CI/CD, automated tests, and release practices
Improve reliability and observability, detect failures and anomalies early, and design recoverable operations
Make governed data usable by AI through metric definitions, Genie spaces, and MCP servers
Validate incoming data using row counts, date spans, expected fields, and historical coverage
Automate recurring data operations and participate in a shared, lightweight data operations rotation
Protect PHI through access controls, auditing, de-identification, and secure data exchange
Provide analytics engineering with a reliable, timely, cost-effective platform
Represent data engineering with partners, vendors, and colleagues and share knowledge

Requirements

What you’ll need

Typically seven or more years building production software or data systems
Several years owning data infrastructure or pipelines end to end, from design through operation
Production experience with at least one distributed data processing engine at scale, such as Spark, Databricks, Snowflake, BigQuery, Flink, Dask, or Ray
Strong Python and defensible SQL skills
Experience designing systems on a major cloud; AWS preferred, including storage, compute, networking, IAM, and cost
Experience with automated testing, CI/CD, infrastructure as code, code review, observability, and incident response
Experience leading technical work and mentoring other engineers
Experience investigating upstream data problems through resolution
Daily use of AI coding agents and ability to identify incorrect AI results on real data
Familiarity with Databricks, Delta Lake, Unity Catalog, and dbt is a bonus
Familiarity with Databricks Genie, MCP servers, or other governed-data approaches for AI agents is a bonus
Healthcare or regulated-data experience, including claims, eligibility, FHIR, HL7 v2, HIPAA, or SOC 2, is a bonus
Experience with workflow orchestration, event-driven ingestion, or serverless compute is a bonus
Experience leading or managing engineers, or interest in growing into a data engineering lead, is a bonus
Must physically reside in the United States
Must answer whether visa sponsorship will be required to maintain employment authorization

Benefits

Comp & perks

Extensive development opportunities
Diverse career paths
Culture valuing diversity, equity, inclusion, and belonging
Innovative payment models and technology-driven community health mission