Senior Manager, Data Engineering

Veracyte, Inc.

. Manage and develop a team of data engineers, including talent planning, hiring, coaching, performance management, career development, and team effectiveness .

Posted 9/21/2026full-timeSan Diego • California • United StatesSenior💰 $199,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing data engineering teams, driving architectural decisions, and ensuring data platform security and compliance. Proficient in AWS services and data pipeline development, with a strong focus on operational excellence and collaboration across multidisciplinary teams.

Highest-signal resume keywords

Data Engineering ManagementAWS Services ProficiencyData Pipeline DevelopmentRegulatory Compliance ExperienceStrong Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonETL/ELT FrameworksData Lake ArchitectureData Quality ImplementationAutomated TestingObservabilityData ModelingDistributed Data ProcessingTechnical Debt Management

Soft Skills

Collaborative LeadershipPerformance ManagementCoachingStakeholder CommunicationTeam Effectiveness

Tools & Technologies

AWS S3AWS GlueAWS AthenaAWS LambdaAWS IAMAWS CloudWatchSnowflakeOrchestration ToolsData Governance ToolsCI/CD Tools

Industry Keywords

BiotechnologyLife SciencesHealthcareRegulated Data EnvironmentsMedical Device RegulationsBioinformatics DataMLOpsData PrivacyLaboratory Information Management SystemsProcess Scaling

Tech Stack

Tools & technologies

AWSETLPythonSQL

About the role

Key responsibilities & impact

Manage and develop a team of data engineers, including talent planning, hiring, coaching, performance management, career development, and team effectiveness
Guide architecture, design reviews, code quality, troubleshooting, and key implementation decisions
Translate business and scientific requirements into platform capabilities, delivery plans, and measurable outcomes
Establish and maintain data platform standards, governance practices, architectural guidelines, and operational processes
Make architectural decisions using AWS services and related technologies such as Snowflake
Improve CI/CD, automated testing, observability, lineage, documentation, security, privacy, and code quality
Partner with Analytics, Data Science, Product, Clinical, Laboratory, Software Engineering, Security, and IT teams
Ensure data-platform security, regulatory compliance, privacy, and quality-management requirements
Drive platform delivery and operational excellence, including production reliability
Balance delivery priorities, operational support, platform enhancements, technical debt, vendors, and resources
Evaluate emerging technologies and recommend adoption
Communicate technical decisions, risks, recommendations, and trade-offs to stakeholders and leaders
Model collaborative and inclusive leadership

Requirements

What you’ll need

Bachelor’s degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience
8+ years of relevant experience in data engineering, software engineering, data platforms, or related fields
5+ years of people-management experience
Experience leading a data engineering department or multiple related disciplines
Experience designing, building, and operating production data pipelines and data platforms, including data lake or lakehouse architectures
Strong working knowledge of AWS services such as S3, Glue, Athena, Lambda, IAM, and CloudWatch, or comparable technologies
Hands-on proficiency with SQL and Python
Experience with ETL/ELT frameworks, orchestration tools, distributed data processing, analytical data modeling, and reusable data products or shared platform capabilities
Experience implementing data quality, automated testing, observability, lineage, security, privacy, and regulatory controls
Experience establishing operational objectives, policies, procedures, work plans, schedules, and resource priorities for a technical team
Experience managing technical debt and operational risk
Ability to collaborate across engineering, scientific, product, clinical, business, Security, and IT teams
Strong communication skills for technical and nontechnical audiences
Preferred: experience in biotechnology, life sciences, diagnostics, healthcare, regulated data environments, medical device regulations, scientific/clinical/laboratory/LIMS/bioinformatics data, ML/AI data workflows, MLOps, AWS optimization, reusable data products, metadata/catalog/lineage platforms, budgets, vendors, resource planning, or process scaling

Benefits

Comp & perks

Competitive compensation and benefits
Potential eligibility for discretionary bonuses/incentives
Potential eligibility for restricted stock units
Career opportunities and growth in a purpose-driven environment
Inclusive workforce and workplace
2024 Certified Great Place to Work recognition