Come make your difference in communities across Canada, where authenticity, trust and making connections is valued - as we shape the future of Canadian retail, together. Our unique position as one of the country's largest employers, coupled with our commitment to positively impact the lives of all Canadians, provides our colleagues a range of opportunities and experiences to help Canadians Live Life Well. As a Staff Data Engineer, you will play a technical leadership and architecture role on the Retail Media Platform team. This is a senior, hands‑on position focused on designing, building, and evolving high‑scale data platforms and backend systems that power advertising measurement, reporting, analytics, and AI‑enabled use cases. You will lead complex design initiatives, improve performance and reliability across critical pipelines, raise the bar on code quality, and mentor engineers across teams. You will also work closely with backend, product, and AI teams to reduce system coupling, evolve metadata and API design, and enable next‑generation data and AI capabilities across the platform. This role is ideal for someone who enjoys being both a system architect and a strong individual contributor, and who wants to shape the future of data and AI platforms at scale. Architecture & Technical Leadership Lead system-level design for scalable, reliable, and high-performance data platforms supporting batch, streaming, and real-time use cases. Drive architectural improvements across data pipelines, metadata layers, APIs, and service dependencies. Partner with Product, Backend, and AI teams to translate complex business requirements into robust technical solutions. Data Engineering & Platforms Architect, build, and optimize large‑scale data pipelines using PySpark, Dataproc, Airflow, GCS, Parquet, and GCP services. Design and maintain data models that support analytics, reporting, experimentation, and measurement at scale. Implement strong data quality, validation, observability,



and monitoring practices to ensure data trust and reliability. Reduce unnecessary API and metadata dependencies to unlock better performance and flexibility, including deeper and more effective use of analytics engines such as Druid. Collaborate closely with backend engineers on service design, scalability, and performance tuning. AI & Data-for-AI Enablement Partner with Data & AI teams to enable AI-driven features through high-quality, well‑modeled, and inference‑ready data pipelines. Support Loblaw's broader AI strategy (including LDIA initiatives) by designing data foundations that power experimentation, automation, and intelligent decision-making. Help bridge traditional data engineering with emerging AI‑enabled use cases. Engineering Excellence & Mentorship Lead design reviews and code reviews, setting standards for performance, readability, testing, and maintainability. Mentor and coach engineers across experience levels, helping raise overall engineering maturity. Drive continuous improvement across pipeline performance, cost efficiency, reliability, and operational excellence. BA/BS in Computer Science, Engineering, Math, or a related field (advanced degree is a plus). Senior- or Staff-level Data Engineer with experience owning production‑critical, large‑scale systems. Deep hands‑on expertise with PySpark and distributed data processing, including performance optimization. Strong experience with cloud data platforms, preferably GCP (Dataproc, GCS, BigQuery). Strong SQL skills with experience querying and optimizing large analytical datasets.



Experience with non‑relational and analytical data stores (e.G., Solid programming experience in Python, Scala, or Java. Experience with orchestration tools such as Airflow and operating production pipelines. Strong understanding of data modeling, partitioning strategies, and storage formats (e.G., Experience working in Agile environments with iterative delivery. Solid oral and written communication skills, with the ability to articulate technical concepts to both technical and non‑technical stakeholders. Experience supporting AI/ML workflows or platforms used for model training or inference. Our commitment to Sustainability and Social Impact is an essential part of the way we do business, and we focus our attention on areas where we can have the greatest impact. Our approach to sustainability and social impact is based on three pillars - Environment, Sourcing and Community - and we are constantly looking for ways to demonstrate leadership in these important areas. We offer our colleagues progressive careers, comprehensive training, flexibility, and other competitive benefits - these are some of the many reasons why we are one of Canada's Top Employers, Canada's Best Diversity Employers, Canada's Greenest Employers and Canada's Top Employers for Young People. We have a long‑standing focus on diversity, equity and inclusion because we know it will make our company a better place to work and shop. We are committed to creating accessible environments for our colleagues, candidates and customers. Requests for accommodation due to a disability (which may be visible or invisible, temporary or permanent) can be made at any stage of application and employment. Candidates who are 18 years or older are required to complete a criminal background check. The Company uses artificial intelligence for the purpose of screening, assessing and/or selecting applicants for this position. #

📌 Data Architect - Fulltime Remote (Toronto)
🏢 Loblaw Digital
📍 Toronto