Analytics Engineer
KUBRA
full-time
Posted on:
Location Type: Hybrid
Location: Mississauga • 🇨🇦 Canada
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudETLPythonSQL
About the role
- Own a curated catalog of business metrics and KPIs, ensuring consistent definitions and alignment across products and clients.
- Design, build, and automate dashboards and reports in Power BI and Looker, backed by robust data models and clear analytical logic.
- Partner with Data Engineering to define reporting datasets, enforce data quality checks, and uphold governance standards.
- Deliver accurate, timely reports and dashboards to stakeholders with high reliability and attention to detail.
- Conduct in-depth analysis to identify trends, drivers, and opportunities, providing actionable recommendations to business leaders.
- Automate recurring reporting processes (e.g., QBRs, client packages) using reusable datasets, templates, and semantic layers.
- Model, query, and transform data using SQL; maintain performant data pipelines, refresh schedules, and access controls.
- Collaborate with Data Science to support experiments and track ML/AI outcomes through production dashboards.
- Partner with cross-functional teams (Product, CXT, Finance, Client Success) to align metrics with company and client goals.
- Document analytical logic, KPI definitions, data lineage, and assumptions to enable self-service and knowledge sharing.
- Implement QA for data assets, including validation, regression testing, and monitoring for anomalies.
- Stay current with BI and analytics tools and best practices; recommend and adopt improvements that enhance reliability, performance, or usability.
Requirements
- 3–5 years of experience in data analysis and reporting, preferably within product or SaaS environments.
- Hands-on proficiency with SQL and Looker.
- Experience building end-to-end reporting solutions from data modeling to dashboard deployment and support.
- Familiarity with LookML, model/view development and performance tuning, data warehousing concepts and ETL/ELT practices; exposure to cloud platforms (AWS/Azure) is preferred.
- Experience collaborating with Data Engineering and Data Science teams; Python/ML/AI experience is an asset.
- Undergraduate degree in a related discipline (e.g., Computer Science, Statistics, Analytics, Mathematics, Engineering, Economics) or equivalent experience.
- Advanced certifications in analytics or BI tools are preferred.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data analysisreportingSQLLookerdata modelingdashboard deploymentETLELTdata warehousingPython
Soft skills
attention to detailcollaborationcommunicationanalytical thinkingproblem-solvingstakeholder managementrecommendation deliveryknowledge sharinggovernance adherencequality assurance
Certifications
advanced analytics certificationBI tools certification