Senior Analytics Engineer
About The Position
Versaterm is a global public safety solutions company helping agencies transform how they serve their communities. Since 1977, we’ve been building an ecosystem of intuitive tools designed for public safety agencies, forensic labs, court systems, schools and other institutions. Through purposeful integrations and a selective growth strategy, we focus on improving workflows to help our customers achieve more efficient operations, better service and more just outcomes. Our teams are driven by innovation, expertise and an unwavering commitment to customer success. As we continue to grow and expand our ecosystem, you’ll have the opportunity to contribute to solutions that enhance community safety and transform the future of public safety technology. If you’re passionate about making a meaningful difference, we’d love to hear from you. We are seeking a Senior Analytics Engineer to architect and evolve Versaterm’s engineering metrics ecosystem. This is a highly technical, hands-on role responsible for building the data platform, integrations, and reporting layer that enables unified engineering visibility across the organization. This role goes far beyond dashboard development. You will design and operationalize the data infrastructure that ensures our engineering metrics are accurate, reliable, automated, and actionable. You will work closely with Engineering and Product leadership to define outcome‑driven KPIs and convert raw operational data into insights that guide strategic decision-making.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Engineering, or a related field
- 8+ years in analytics engineering, data engineering, or technical analytics roles
- Strong experience with SQL and data transformation tools (e.g., dbt or similar)
- Proven experience integrating data from systems such as Jira, Azure DevOps, GitHub, CI/CD pipelines
- Expertise building dashboards in BI platforms (Power BI, Tableau, Looker, or similar)
- Experience designing scalable, production-quality data models and semantic layers
- Working knowledge of APIs, Python (or similar), automation frameworks, ELT/ETL concepts
- Strong understanding of the software development lifecycle, DevOps metrics, and engineering processes
- Ability to translate complex engineering datasets into clear insights for senior leadership
- A practical, execution-focused mindset with a drive to create durable, repeatable solutions
- Note: This position requires a security clearance from the Government of Canada. Candidates must be legally authorized to work in Canada and must successfully obtain and maintain a Reliability security clearance. Please note that specific customer contracts may impose additional security verification requirements. Obtaining and maintaining all required security clearances is a condition of employment. For more information on the Government of Canada's security screening process, please visit Public Services and Procurement Canada.
Responsibilities
- Build and evolve a scalable engineering analytics ecosystem
- Architect the data infrastructure, semantic layer, and source integrations required for unified engineering metrics.
- Implement and maintain data pipelines, transformations, APIs, and automation to ensure high-quality, consistent data.
- Develop standardized engineering KPIs and dashboards
- Develop standardized engineering KPIs and dashboards
- Integrate data across engineering and product systems
- Jira, Confluence, Azure DevOps, GitHub, CI/CD tools
- Aha! (or similar roadmap tooling)
- Incident/support systems where applicable
- Build repeatable data ingestion via APIs, webhooks, and scheduled pipelines
- Ensure data quality and governance
- Implement validation frameworks and data quality checks
- Enforce metric definitions, naming conventions, and data modeling standards
- Maintain a source-of-truth metrics layer consumable by BI tools
- Deliver insights and partner with leadership
- Create executive-ready analytics, narratives, and recommendations
- Partner with Engineering Directors, to align on KPI definitions
- Identify trends, bottlenecks, and improvement opportunities to support engineering excellence
- Continuously improve
- Enhance models, pipelines, and metrics as tooling and processes mature
- Champion automation and reduce manual reporting across engineering
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What This Job Offers
Job Type
Full-time
Career Level
Senior
