Analytics Engineer
Role Overview
The Analytics Engineer is a full-stack data professional owning data from ingestion and transformation to modeling, analysis, and insight delivery.
The role combines data analyst and data engineer work to provide clean, reliable, analytics-ready data and timely insights.
The engineer creates scalable data models, supports BI teams, and works with business stakeholders to turn raw data into decisions.
Key Skills for This Role
Full Job Posting
About Metro Supply Chain
Metro Supply Chain provides integrated, data-driven supply chain solutions, operating across North America and Europe.
The company reports more than 190 sites and 22.5 million square feet of operations, with a team of 9,000.
Role summary
The Analytics Engineer is a full-stack data professional owning data from ingestion and transformation to modeling, analysis, and insight delivery.
The role combines data analyst and data engineer work to provide clean, reliable, analytics-ready data and timely insights.
The engineer creates scalable data models, supports BI teams, and works with business stakeholders to turn raw data into decisions.
Responsibilities
- Own the end-to-end data lifecycle, including extraction, cleaning, transformation, and validation across systems.
- Build reusable ELT/ETL pipelines, analytics-ready datasets, and support cloud data infrastructure using Azure and Snowflake.
- Build and maintain scalable data models; define business-friendly metrics, dimensions, and standardized logic.
- Document data lineage and transformation logic for transparency and governance.
- Analyze trends and performance issues; use Python or SQL to automate recurring analysis and support forecasting or trend detection when needed.
- Identify data quality gaps and recommend improvements.
- Build and optimize Power BI dashboards and reports; communicate findings through clear visuals and business-ready narratives.
- Partner with stakeholders across Supply Chain, Operations, and Finance.
- Collaborate with data engineers, analysts, and business teams to define requirements and improve reliability, performance, and scalability.
- Communicate findings to technical and non-technical audiences and participate in agile ceremonies, sprint reviews, and data governance activities.
Experience and education
- 3–5 years of experience.
- University or college degree in Data Science, Analytics, Software Engineering, Computer Science, Mathematics, or a related field.
- Experience using SQL for data extraction and transformation.
- Familiarity with Python or R for scripting, automation, and exploratory analysis.
- Experience with BI tools such as Power BI, Tableau, or Looker.
- Understanding of ETL/ELT concepts, cloud data platforms, and data modeling.
- Certifications in Power BI, SQL, Azure, Snowflake, or Python are an asset.
- Strong communication skills and an analytical mindset.
Benefits
- Medical, dental, and vision coverage; life and disability insurance; wellness programs; and a retirement savings program with company match.
- Additional offerings include a team wear allowance, employee appreciation day, company-sponsored social events, and community volunteering.
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