Senior Data Engineer

Experience Level: Senior (5+ years)

Retailogists is a fast-growing startup at the intersection of retail consulting and technology. We combine deep retail domain expertise with technical excellence in big data, full-stack engineering, and AI/ML. Our clients range from fast-scaling digital brands to large, multi-location retailers.

We’re a nimble team of technologists, consultants, and builders – and we’re looking for a Senior Data Engineer who is passionate about data and eager to make an impact. This role will entail a large Analytics and BI component as well.

What You'll Do

As a Senior Data Engineer at Retailogists, you'll play a critical role in building and scaling our data infrastructure, both for internal tools and client-facing platforms. You’ll be responsible for designing and maintaining scalable data pipelines, enabling analytics, and contributing to a robust data platform that supports BI and AI workloads.

Responsibilities include:

Designing and maintaining high-quality ETL/ELT pipelines across multiple data sources

Modelling and transforming data for analytics use cases (data lakes, warehouses, semantic layers)

Supporting and building BI and analytics workflows, including metric definitions and dashboarding

Collaborating with engineers, analysts, and data scientists to deliver end-to-end solutions

Contributing to internal data platform components and reusable tooling

Working directly with clients to deliver end-to-end solutions and reports

What We're Looking For

5+ years of professional experience in data engineering or analytics engineering

Deep understanding of data engineering concepts: ETL, data lakes, data warehousing, orchestration

Advanced SQL skills – capable of writing efficient, scalable queries for large datasets

Proficiency with Spark and Pandas

Strong interest in analytics and BI – a significant part of this role involves analytics engineering

Deep experience with at least one BI tool (Metabase, Looker Studio, PowerBI etc.)

Experience with cloud-native data platforms (BigQuery, Snowflake, Redshift, etc.)

Familiarity with DBT and semantic layer modelling

Work Environment

Distributed team with offices in Kitchener ON and Montreal QC

Flexible hours, collaborative culture, and high-impact work

High levels of autonomy with potential for career growth on multiple tracks