SUMMARYThe Analytics Engineer acts as a
full-stack data professional, owning the end-to-end flow of data-from ingestion and transformation to modeling, analysis, and insight delivery. This role blends the strengths of a Data Analyst and a Data Engineer, ensuring the business has
clean, reliable, analytics-ready data and the ability to unlock insights quickly and independently.
The Analytics Engineer creates scalable data models, supports BI teams, and works directly with business stakeholders to turn raw data into decisions. (existing role)
RESPONSIBILITIESFull-Stack Data Work (End-to-End Ownership): Own the full data lifecycle from raw ingestion to final insight:
- Extract, clean, transform, and validate datasets across systems
- Build robust, reusable data pipelines (ELT/ETL) with modern tools
- Create analytics-ready datasets for BI and business teams
- Support cloud data infrastructure (Azure, Snowflake)
Data Modeling & Semantic Layer Development- Build and maintain scalable data models used by reporting and analytics teams
- Define business-friendly metrics, dimensions, and standardized logic
- Document data lineage and transformation logic for transparency and governance
Advanced Analytics & Insight Generation- Analyze data to identify trends, diagnose performance issues, and support decision-making
- Use Python/SQL to automate recurring analytical tasks
- Support predictive or prescriptive analytics when needed (e.g., forecasting, trend detection)
- Proactively spot data quality gaps and recommend improvements
BI Enablement & Visualization- Build, maintain, and optimize Power BI dashboards and reports
- Translate complex data into clear visuals and business-ready narratives
- Act as a partner to business stakeholders across Supply Chain, Operations, and Finance
Cross-Functional Collaboration- Work with Data Engineers to ensure reliability, performance, and scalability
- Work with Analysts and business teams to define requirements and close knowledge gaps
- Communicate findings to technical and non-technical audiences
- Participate in agile ceremonies, sprint reviews, and data governance activities
EXPERIENCE AND EDUCATION - 3- 5 years of experience
- University/College degree in Data Science, Analytics, Software Engineering, Computer Science, Math, or related field
- Certifications in Power BI, SQL, Azure, Snowflake, or Python are an asset
- Experience in SQL for data extraction and transformation
- Familiarity with Python or R for scripting, automation, and exploratory analysis
- Experience with BI tools (Power BI, Tableau, Looker)
- Understanding of ETL/ELT concepts, cloud data platforms, and data modeling
- Strong communication skills and an analytical mindset
Why Join Us- Work in an environment where safety is our first priority
- The opportunity to build a career with a growing company
- Medical, dental, and vision coverage for you and your family
- Life and disability insurance
- Wellness programs to support your family's well-being
- A Retirement Savings Program with a company match
- Company team wear allowance
- Employee Appreciation Day
- Company sponsored social events
- Community volunteering
