Data Engineering - Manager
- Robot Insight Tech
2 Days Ago
NA
NA
Palo Alto-CA
13-16 Years
Required Skills: HL7, FHIR, EDI, HIPAA, CLIA, CAP, FDA, data engineer lead
Job Description
Role : Data Engineering - Manager
Location : Palo Alto,CA | Onsite role
Location : Palo Alto,CA | Onsite role
Responsibilities:
Leading and mentoring a growing team of engineers working on data ingestion, processing, and integration
Designing and delivering cloud-native data pipelines using Python, AWS, and Kubernetes
Architecting robust ETL/ELT frameworks that interact with systems such as Epic, OncoEMR, and LIMS
Ensuring secure, scalable, and compliant data flows in accordance with HIPAA, CLIA, CAP, and FDA regulations
Driving engineering best practices in CI/CD, automated testing, and observability (metrics, alerts, dashboards)
Collaborating closely with clinical operations, product managers, compliance teams, and external healthcare partners
Defining KPIs and SLAs to measure and maintain pipeline performance and data availability
Managing integration with healthcare data standards including HL7, FHIR, and EDI formats
Required Qualifications:
10+ years of experience in software/data engineering; at least 3+ years in technical leadership or engineering management
Strong hands-on expertise in Python, along with cloud platforms like AWS and container orchestration tools like Kubernetes
Experience with MuleSoft or similar integration platforms
Proven success integrating with healthcare systems such as Epic, OncoEMR, and laboratory data systems
Deep understanding of healthcare data protocols (HL7, FHIR, EDI) and regulatory standards (HIPAA, CLIA, CAP, FDA)
Proficiency in DevOps and CI/CD practices for data pipelines
Exceptional problem-solving, communication, and cross-functional collaboration skills
Preferred Experience:
Background in diagnostics, bioinformatics, or healthcare IT
Experience working in a highly regulated environment with clinical trial data or laboratory workflows
Familiarity with data observability tools (e.g., Datadog, Prometheus, OpenTelemetry)
Leading and mentoring a growing team of engineers working on data ingestion, processing, and integration
Designing and delivering cloud-native data pipelines using Python, AWS, and Kubernetes
Architecting robust ETL/ELT frameworks that interact with systems such as Epic, OncoEMR, and LIMS
Ensuring secure, scalable, and compliant data flows in accordance with HIPAA, CLIA, CAP, and FDA regulations
Driving engineering best practices in CI/CD, automated testing, and observability (metrics, alerts, dashboards)
Collaborating closely with clinical operations, product managers, compliance teams, and external healthcare partners
Defining KPIs and SLAs to measure and maintain pipeline performance and data availability
Managing integration with healthcare data standards including HL7, FHIR, and EDI formats
Required Qualifications:
10+ years of experience in software/data engineering; at least 3+ years in technical leadership or engineering management
Strong hands-on expertise in Python, along with cloud platforms like AWS and container orchestration tools like Kubernetes
Experience with MuleSoft or similar integration platforms
Proven success integrating with healthcare systems such as Epic, OncoEMR, and laboratory data systems
Deep understanding of healthcare data protocols (HL7, FHIR, EDI) and regulatory standards (HIPAA, CLIA, CAP, FDA)
Proficiency in DevOps and CI/CD practices for data pipelines
Exceptional problem-solving, communication, and cross-functional collaboration skills
Preferred Experience:
Background in diagnostics, bioinformatics, or healthcare IT
Experience working in a highly regulated environment with clinical trial data or laboratory workflows
Familiarity with data observability tools (e.g., Datadog, Prometheus, OpenTelemetry)
