Senior Analytics Engineer

Chainguard is hiring a Senior Analytics Engineer to build and evolve the data foundation that powers company-wide decisions. The role owns analytics infrastructure, data models, and self-service data products while partnering with stakeholders to deliver trusted, scalable data solutions.

Responsibilities:

• Own and evolve core components of our analytics platform, including data models, pipelines, metric definitions, semantic layers, and self-service reporting experiences
• Design, build, and maintain scalable, reliable data models and transformations using dbt and modern analytics-engineering practices
• Develop trusted sources of truth that support decision-making across the company, balancing immediate business needs with long-term scalability and maintainability
• Partner directly with stakeholders to gather requirements, understand business problems, translate needs into technical solutions, and communicate tradeoffs clearly
• Build and improve dashboards, analytical tools, and enablement materials that help business partners understand, explore, and confidently use data independently
• Own the full lifecycle of data products: discovery, design, implementation, testing, documentation, deployment, monitoring, governance, and iteration
• Improve the reliability, observability, performance, and data quality of ELT workflows and integrations across our modern data stack
• Establish and raise standards for data modeling, testing, documentation, lineage, governance, access controls, and metric consistency
• Use AI thoughtfully to improve analytics workflows, enable new forms of analysis, and help the business get more value from its data
• Independently triage technical and data-quality issues, identify root causes, and drive durable resolutions without requiring day-to-day direction
• Mentor and support more junior analytics teammates through technical guidance, code review, knowledge sharing, and reusable patterns
• Help shape the technical roadmap for a growing Analytics function by identifying opportunities for automation, process improvement, and scalable platform investments

Requirements:

• 5+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a closely related field; equivalent depth of experience will also be considered
• Demonstrated success leading complex, cross-functional data initiatives from ambiguous problem definition through delivery, adoption, and measurable business impact
• Advanced SQL skills and deep experience designing, building, and operating analytical data models and pipelines
• Strong hands-on experience with dbt and modern analytics-engineering practices, including testing, version control, documentation, orchestration, observability, and data quality management
• Experience working with modern ELT and activation tools such as Fivetran and Hightouch, or comparable technologies
• Experience with cloud data platforms and warehouses
• Experience with business intelligence and semantic-layer tools such as Omni, Looker, Sigma, Tableau, Mode, Hex, or similar platforms
• Demonstrated ability to turn complex technical concepts and data into clear, actionable guidance for non-technical stakeholders
• Practical experience using AI in data, analytics, engineering, or business workflows, along with sound judgment about where it creates meaningful value
• Strong understanding of dimensional and analytical data modeling, metric governance, lineage, access controls, and trusted-source-of-truth practices
• Ability to balance technical rigor with pragmatism: you know when to build for scale and when to deliver a simpler solution quickly
• Experience mentoring, reviewing work, and helping other technical teammates grow
• Excellent communication, stakeholder-management, and problem-solving skills
• Comfort operating independently in a fast-moving, ambiguous environment with evolving priorities
• Curiosity, initiative, and a builder mindset
• Experience with Google Cloud Platform and BigQuery is strongly preferred
• Omni experience is a plus
• Startup or high-growth-company experience is preferred, but not required
• Experience with Python or another quantitative programming language