Data Engineer

Architect, design, implement, enhance, and maintain highly scalable, available, secure, and elastic cloud‑ready data solutions using cutting‑edge technologies to support predictive and prescriptive analytics needs. Act as an expert in our data domains and a trusted partner to solutions architects and data scientists, playing a crucial role in the analytics solution lifecycle—from prototype to production and operations in areas such as promotions, supply and demand planning, item/menu‑level analytics, supply chain simulations, and optimization.

• Collaborate with data management, data science, decision science, and technology teams to address supply chain data needs in demand‑ and supply‑planning, replenishment, pricing, and optimization.
• Develop and refine data requirements, design and build data deliverables, and optimize data pipelines in both non‑production and production environments.
• Design, build, and monitor data pipelines covering data transformation, models, schemas, metadata, and workload management.
• Integrate analytics and data science outputs into business processes and workflows.
• Build and optimize ETL/ELT pipelines, including data replication, CI/CD, and API design and access.
• Improve existing ETL processes and data integration flows, moving them to production.
• Use popular data discovery, analytics, and BI or AI tools in semantic‑layer data discovery.
• Apply agile methodologies and Dev Ops/Data Ops principles to improve communication, integration, reuse, and automation between data managers and consumers.
• Implement Agentic AI capabilities to drive efficiency and opportunity.

• Bachelor’s degree in computer science, data management, information systems, or a related field; advanced degree preferred.
• 3+ years of data engineering experience building production data pipelines (batch and/or streaming) with Spark on cloud.
• 2+ years of hands‑on Azure Databricks (PySpark/Scala, Spark SQL, Delta Lake) including Delta Lake operations and Unity Catalog management.
• Experience with Azure Data Factory orchestration and integration with ADLS Gen2, Key Vault.
• Strong SQL across large datasets with performance tuning skills.
• Experience in data quality at scale, monitoring, alerting, and playbooks.
• Dev Ops for data:
  Git branching, code reviews, unit/integration testing, CI/CD with Azure Dev Ops or Git Hub Actions.
• Infrastructure as Code using Terraform or Bicep for Databricks, ADF, and storage.
• Observability and cost control using Azure Monitor/Log Analytics, autoscaling, Photon, and cost/performance trade‑offs.
• Proven collaboration with cross‑functional stakeholders in analytics, governance, product, and security.

• Compensation: $95,000–$110,000 base with a 5% targeted bonus.
• Generous extended healthcare benefits.
• Paid parental and medical leave programs.
• RRSP and DPSP benefits with company match and profit sharing.
• 15 days of paid time off plus company holidays.
• Hybrid work model with flexibility.
• Tuition reimbursement.
• Inclusive employee resource groups.
• Opportunities for learning and development, recognition, and corporate culture initiatives.

We are an equal opportunity employer and value diversity. We do not discriminate based on race, religion, color, national origin, sex, gender identity or expression, sexual orientation, age, marital status, veteran status, or disability status. Reasonable accommodations are provided for applicants with disabilities.