Define and implement organization-wide data quality standards, including data contracts, SLAs, and governance frameworks across domains
Design and scale reliability and observability frameworks, including SLI/SLO models, lineage tracking, monitoring, and alerting patterns
Establish and evolve incident management practices, including severity models, escalation paths, on-call structures, and blameless postmortems
Develop and standardize data engineering SDLC practices, including testing strategies, CI/CD, versioning, and reusable frameworks
Drive cross-functional prioritization of reliability initiatives, balancing technical debt, operational health, and product delivery across teams
Lead ecosystem-wide platform improvements, identifying architectural gaps, reducing fragmentation, and influencing build vs buy decisions
Own and deliver complex, high-impact data initiatives, aligning stakeholders, mitigating risks, and driving scalable solutions in ambiguous environments

Extensive experience designing and operating scalable data platforms with a focus on reliability, quality, and observability
Experience leveraging AI tools and methodologies to design and implement the solutions
Deep expertise in data architecture, including data modeling, pipeline design, and distributed data systems
Proven ability to define and implement data quality frameworks, including SLAs, data contracts, and governance standards
Strong experience establishing SLI/SLO frameworks, monitoring, and alerting for large-scale data systems
Demonstrated ability to lead complex, cross-team technical initiatives and drive alignment across stakeholders
Experience defining and scaling engineering best practices, including testing, CI/CD, and development standards for data systems

Senior Staff Data Engineer

Key skills