Senior Analytics Engineer, Sigma Computing

• 4+ years of experience in analytics engineering or equivalent role, with experience supporting technical teams
• Strong proficiency in SQL (dbt experience preferred) with a deep understanding of dimensional modeling and transformation design for engineering and support use cases
• Experience working with engineering and support systems (e.g., Jira, Intercom, ZenDesk, CI/CD Platforms, etc)
• Strong grasp of cloud data warehouses (Snowflake or Databricks preferred) and data version control (git)
• Demonstrated experience supporting Engineering and / or Technical Support stakeholders at a B2B SaaS company (Bonus: experience in other high-growth environments is also valued)
• Experience with data visualization tools (Sigma experience preferred - you will use Sigma every day!)
• Excellent communication skills, especially in explaining complex data concepts to technical and non-technical stakeholders
• Self-starter with high attention to detail and the ability to manage multiple priorities in a fast-paced environment
• Proven ability to influence cross-functional stakeholders and drive adoption of data solutions across technical and business teams

Desirable

• With 3.5x growth in ARR and a maturing operating model, Sigma is looking for a curious and collaborative Senior Analytics Engineer to support our Engineering and Technical Support teams
• In this role, you’ll enable data-driven decision-making through robust data modeling, reporting, and infrastructure development
• You’ll partner closely with Technical Support and Engineering teams to improve operational efficiency, enhance customer insights, and build scalable data solutions for engineering operations
• Design, build, and maintain core data models to power critical Technical Support and Engineering workflows including system performance metrics, incident response data, customer support interactions, and operational telemetry
• Model incident tracking data to improve response times for critical outages and system issues while measuring the effectiveness of process improvements and operational changes
• Identify opportunities to develop new self-service and data apps tools that streamline engineering operations and support team workflows
• Create comprehensive documentation for data models, pipelines, and workbooks to enable self-service data discovery and maximize user adoption across teams
• Analyze support request patterns and complexity trends to inform capacity planning and identify opportunities for process optimization as customer needs evolve
• Partner closely with Engineering and Technical Support stakeholders to gather requirements and translate them into scalable data products that enhance decision-making, operational visibility, and team efficiency
• Mentor team members and cross-functional partners on analytics best practices while establishing and maintaining data quality standards across all deliverables
• Drive continuous improvement initiatives by analyzing workflow inefficiencies and recommending data-driven solutions that reduce manual processes and improve team productivity
• Deliver reporting and dashboards in Sigma to enable real-time insights into system performance, customer health metrics, and operational KPIs for leadership decision-making