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Garner Health, LLC · 2 days ago

Staff Data Engineer

New York, NY

Full-time

Hybrid

Senior Level, Lead/Staff

$240K/yr - $260K/yr

7+ years exp

Garner Health is a rapidly growing company focused on reshaping the healthcare economy by evaluating doctor performance and controlling costs. They are seeking a Staff Data Engineer to lead a team in building scalable data infrastructure that supports analytics and improves healthcare outcomes.

Hospital & Health Care

No H1B

Responsibilities

Shape the technical roadmap and lead architectural decisions for scalable, resilient data infrastructure that supports analytics, external products, and millions of users

Design compliant, cost-effective systems that balance performance, maintainability, and rapid feature development in a healthcare setting

Build high-impact data platforms, pipelines, and observability tools that ensure HIPAA compliance, governance, and 99.9% uptime for mission-critical systems

Partner cross-functionally with Product, Engineering, Data Science, and Research to deliver user-facing features, empower teams with self-service frameworks, and translate technical decisions into business impact

Elevate team excellence by mentoring engineers, establishing coding and architectural standards, and fostering a culture of testing, monitoring, and operational rigor

Qualification

Data EngineeringPythonAWSETL/ELT PipelinesSQLData GovernanceCloud Data ArchitecturesPipeline OrchestrationTeam LeadershipMentoringCommunication Skills

Required

7+ years of software engineering experience with 3+ years specifically in Data Engineering, including experience leading technical initiatives that directly impacted business metrics

Proven track record of building and scaling data platforms that support analytical workloads

Experience designing systems that balance competing priorities: performance, cost, compliance, and developer velocity

Advanced proficiency in Python and SQL, with experience optimizing complex queries and data transformations at scale

Hands-on experience building production ETL/ELT pipelines using tools like Spark, Beam, or AWS Glue that process terabytes of data daily

Deep understanding of cloud data architectures, preferably AWS, including experience with Kubernetes for container orchestration

Experience with pipeline orchestration tools (Airflow, Argo, Dagster) managing workflows with complex dependencies and SLAs

Working knowledge of modern Data Lake formats (Apache Iceberg, Hudi) and data governance tools that ensure data quality and lineage

Proficiency with analytics platforms like Snowflake, BigQuery, or Trino for large-scale data processing and performance optimization

Experience building data systems in highly regulated environments (HIPAA, GDPR) with strong security and privacy controls

Demonstrated success in fast-growing startup environments where you've helped scale both systems and teams

Ability to influence technical decisions across multiple teams and communicate complex architectural concepts to both technical and business stakeholders