Senior Manager, Data Engineering (AWS)

Location: Hybrid in the San Diego office or remote within the United States; an additional office-based salary range is listed for South San Francisco.

Salary: $199,000–$220,000 USD annually for the San Diego office; $202,000–$258,000 for South San Francisco; $192,825–$220,000 for remote candidates.

Company

hirify.global is a diagnostics company developing genomic and clinical data-driven cancer tests supported by bioinformatics, AI, and evidence-generation capabilities.

What you will do

• Lead and develop a data engineering team, including hiring, coaching, performance management, career development, and staffing.
• Guide architecture, design reviews, implementation decisions, code quality, troubleshooting, and production operations.
• Build and evolve enterprise data lake and lakehouse platforms using AWS services such as S3, Glue, Athena, Lambda, IAM, and CloudWatch, along with Snowflake.
• Translate scientific, clinical, business, and operational requirements into secure, scalable, maintainable platform capabilities.
• Establish standards for governance, data quality, testing, observability, lineage, security, privacy, and regulatory compliance.
• Drive reliable platform delivery while managing technical debt, operational risk, vendor relationships, budgets, and resource priorities.

Requirements

• 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 with responsibility for objectives, planning, performance, development, and staffing.
• Experience designing, building, and operating production data pipelines and data lake or lakehouse architectures.
• Strong knowledge of AWS data services or comparable technologies, with hands-on proficiency in SQL and Python.
• Experience with ETL/ELT, orchestration, distributed processing, data modeling, automated testing, observability, lineage, security, privacy, and regulatory controls.

Nice to have

• Experience in biotechnology, life sciences, diagnostics, healthcare, or other regulated data environments.
• Experience with medical device regulations, quality-management systems, scientific, clinical, laboratory, LIMS, or bioinformatics data.
• Familiarity with ML/AI data workflows and MLOps platforms.
• Experience with metadata management, data catalogs, lineage platforms, vendors, budgets, or resource planning.

Culture & Benefits

• Purpose-driven work focused on improving cancer care and supporting clinical decision-making.
• Inclusive workplace with emphasis on collaboration, empathy, integrity, quality, and responsible use of resources.
• Competitive compensation and benefits, with potential eligibility for discretionary bonuses, incentives, and restricted stock units.
• Career development opportunities within a growing diagnostics company.