Senior Analytics Engineer - Engineering

Senior Analytics Engineer

Employment Type:

Location Type:

Salary:

Position Overview

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.

We welcome candidates from a variety of backgrounds and experiences—even if you don’t meet every listed requirement, we encourage you to apply. If you’re excited about analytics engineering and want to make an impact at a high-growth company, let’s chat!

Responsibilities

• 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.

Qualifications We Need

• 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.

Bonus Points

• Prior experience with customer sentiment analysis using natural language processing (NLP) techniques on unstructured data such as chat transcripts.
• Experience building robust data pipelines and predictive models.
• Exposure to optimization strategies to improve run-time performance of data models built on high-volume telemetry data.
• Familiarity with data quality and

Application Instructions

(No specific application instructions were provided in the original text.)

Company Information

(No specific company information was provided in the original text.)