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Salary
$61k – $76k per year
Location
In office (Langley)
Seniority
Junior · 2+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 1, 2026. First seen by Alion on Oct 30, 2026. Pattison Food Group scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Pattison Food Group is a Jim Pattison business and Canada’s largest Western-based provider of food and health products.

Come join Pattison Food Group Ltd., a Jim Pattison business, and Canada’s largest Western-based provider of food and health products.

Pattison Food Group Ltd. consists of Save-On-Foods and other well-known grocery banners. With nearly 300 retail locations, we proudly employ more than 30,000 team members.

We have an exciting opportunity for a full-time Data Engineer to join our IT team in Langley, BC.

Reporting to the Team Lead, Data & Analytics, you will be responsible for working with one of the largest, most comprehensive datasets in Canada while delivering and pioneering solutions that will disrupt the retail industry using the latest tools and technologies.

You will be responsible for:

  • Building and maintaining scalable, well-structured data solutions using Medallion Architecture in modern delta lake/lakehouse platforms
  • Designing and developing, high-performance, scalable data pipelines using Databricks, Spark, Python/PySpark and SQL
  • Developing dimensional and analytical data models, including fact and dimension tables, slowly changing dimensions, incremental processing, change data capture, and reusable curated datasets.
  • Writing production Python/Scala scripts in a Spark/Databricks environment to support the data pipelines that feed Machine Learning models
  • Orchestrating data ingestion, transformation, scheduling, monitoring, and recovery processes using ADF / Databricks Automation Bundles
  • Applying data-quality, testing, documentation, security, and governance standards throughout the development lifecycle.
  • Optimizing data pipelines and models to improve performance, scalability, reliability, and cost efficiency. Identifying opportunities to simplify processing and improve overall solution design.
  • Using version control, code reviews, CI/CD, and established release-management practices.
  • Working with business and technical partners to understand requirements and translate them into practical data solutions.
  • Troubleshooting production issues and contributing to ongoing platform and process improvements.

You have:

  • A Bachelor’s degree in a STEM discipline at minimum, a Master’s is preferred.
  • A minimum 2 years of experience building and supporting production data pipelines in a cloud-based environment
  • Strong SQL and Python/PySpark skills, with experience working with large datasets.
  • Experience with Databricks, Spark, Delta Lake, or a comparable modern data platform.
  • Experience with data pipeline orchestration using Azure Data Factory, Databricks Jobs, or similar tools.
  • Knowledge of modern data architecture, ETL/ELT, data modelling, incremental processing, data quality, and production support.
  • Familiarity with Git-based version control, automated testing, and CI/CD practices.
  • The ability to communicate clearly, document solutions, and work effectively with technical and non-technical partners.

You are:

  • A practical problem solver with an ownership mindset.
  • Detail-oriented and committed to delivering reliable, supportable solutions.
  • A collaborative communicator who works well across teams.
  • Curious and adaptable, with an interest in modern data technologies and continuous improvement.

What we offer

In addition to a highly competitive salary, we offer a great range of benefits, a company pension plan, free parking, exclusive team member offers, and opportunities for development and career progression.

If you’re looking to join a team that puts people first, you’re in the right place. Apply online today!

IND6

Compensation Details:

$85,062.00 - $106,328.00

The compensation offered for this position will take into consideration location, education, skills, experience and other factors.

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