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Loblaw Digital

Staff Data Engineer

Toronto, ON, Canada

$145,000.00 - $195,000.00 / 145.000,00$ - 195.000,00$ (per year / par an) · Full-time

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Job details

Pay: $145,000.00 - $195,000.00 / 145.000,00$ - 195.000,00$ (per year / par an)
Job type: Full-time
Apply by: Nov 10, 2026
Posting language: English
Posted: Oct 11, 2026

Original job description

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®.

At Loblaw Companies Limited, we succeed through collaboration and commitment and set a high bar for ourselves and those around us. Whether you are just starting your career, re-entering the workforce, or looking for a new job, this is where you belong.

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.

What You'll Do

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.

Backend & API Enablement

Contribute to the design and evolution of backend services and APIs that expose measurement, filtering, and reporting capabilities.
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.

Does This Sound Like You?

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., Druid, Bigtable, Elasticsearch, or similar).
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., Parquet).
Experience working in Agile environments with iterative delivery.
Strong oral and written communication skills, with the ability to articulate technical concepts to both technical and non-technical stakeholders.
Proven team player who thrives in a fast-paced, collaborative environment.

Nice to Have

Experience supporting AI/ML workflows or platforms used for model training or inference.
Experience with real-time or streaming systems (e.g., Kafka or similar).
Experience in advertising technology, retail media, or large-scale measurement systems.
Experience designing or evolving metadata-driven systems and APIs.

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. Our CORE Values – Care, Ownership, Respect and Excellence – guide all our decision-making and come to life through our Blue Culture. 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 & Canada’s Top Employers for Young People.

If you are unsure whether your experience matches every requirement above, we encourage you to apply anyway. We are looking for varied perspectives which include diverse experiences that we can add to our team.

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. We encourage candidates to make their accommodation needs known so that we can provide equitable opportunities.

Please Note

Candidates who are 18 years or older are required to complete a criminal background check. Details will be provided through the application process.

Hiring Range / Échelle Salariale à L’embauche

$145,000.00 - $195,000.00 / 145.000,00$ - 195.000,00$ (per year / par an)

A candidate’s experience and knowledge as well as the geographical region in which the position is located may be factored into the pay a candidate receives for this position. This posting is for an existing vacancy. The Company uses artificial intelligence for the purpose of screening, assessing and/or selecting applicants for this position. / L’expérience et les connaissances d’un candidat ainsi que la région géographique dans laquelle le poste est situé peuvent être prises en compte dans la rémunération qu’un candidat reçoit pour ce poste. Cette offre d’emploi concerne un poste vacant existant. L’entreprise utilise l’intelligence artificielle dans le but de filtrer, d’évaluer et/ou de sélectionner les candidats à ce poste.

#EN

#SS #LD #ON

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More about this job

Responsibilities

Lead the architecture and hands-on development of scalable data platforms, pipelines, and backend APIs supporting analytics, advertising measurement, reporting, and AI use cases. Improve performance, reliability, data quality, and engineering standards while partnering with product, backend, and AI teams and mentoring engineers.

Requirements

The role calls for senior- or staff-level experience owning production-critical, large-scale systems, with strong hands-on expertise in PySpark, distributed processing, SQL, and cloud data platforms, preferably GCP. Candidates should also bring programming and orchestration experience, knowledge of data modeling and analytical data stores, and strong communication and collaboration skills; a bachelor's degree in a related field is requested, with an advanced degree considered a plus.

Skills

PySpark
Distributed Data Processing
Google Cloud Platform
Dataproc
Google Cloud Storage
BigQuery
SQL
Python
Scala
Java
Apache Airflow
Data Modeling
Data Pipeline Optimization
Druid
Data Quality and Observability
Technical Leadership

Benefits

Comprehensive Training
Flexible Work Arrangements
Competitive Benefits

Visa sponsorship

Not detected in the job text

Keywords

Retail Media
Advertising Measurement
Data Engineering
Data Platform Architecture
PySpark
Distributed Data Processing
Google Cloud Platform
Dataproc
Google Cloud Storage
BigQuery
Apache Airflow
Parquet
Druid
Bigtable
Elasticsearch
SQL
Python
Scala
Java
Data Modeling
Batch Processing
Streaming Systems
Real-Time Data
Data Quality
Observability
API Design
Metadata-Driven Systems
AI and Machine Learning
Agile
Performance Optimization

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