Senior Data Engineer

Job summary

Design and standardize data models, own production ETL/ELT pipelines and the data warehouse, and build reporting infrastructure, dashboards, and business metrics. Partner with engineering and other teams to improve data collection and establish scalable foundations for operational reporting, product analytics, and machine learning evaluation.

Job details

Senior Data Engineer required by an exciting, fast-growing, VC-backed technology business looking to build and scale its data infrastructure as it continues to grow. The business is developing innovative AI-powered technology, processing large volumes of data generated from connected devices, customer activity and in-house machine learning models. As the business continues to scale, they're looking for a Senior Data Engineer to take ownership of how data is collected, structured, modelled and used across the organisation. You'll play a key role in building the foundations of the company's data function, developing scalable data models, owning production ETL pipelines and creating the reporting infrastructure that engineering, product and commercial teams rely on. This is a hands-on opportunity for someone who enjoys building from the ground up, working across technical teams and having a genuine influence over how a growing technology business uses data. What we offer Competitive salary of CAD $100k-$150k + employee stock options 100% employer-covered health benefits Gym membership Catered lunches (3 days a week) Unlimited paid vacation and flexible working hours Hybrid working model (3 days in the office) Dog-friendly office and free on-site parking Relocation support for the right candidate Significant ownership and the opportunity to shape and grow the data function Responsibilities Design and standardise data models across the business, ensuring teams work from consistent and reliable data Build, manage and maintain production ETL/ELT pipelines, moving data from multiple systems into the data warehouse Own the data warehouse, reporting and BI layer, ensuring teams have access to accurate and actionable insights Define core business metrics and develop dashboards that support engineering, product and commercial decision-making Partner with engineering teams to improve product instrumentation and data collection at source Build data foundations that support production metrics, monitoring and operational reporting Help shape the future direction of the data function, including tooling, infrastructure and potential team growth Support the development of product analytics, machine learning evaluation infrastructure and advanced measurement capabilities Requirements 6+ years of experience in Data Engineering, Analytics Engineering or Data Science with a strong engineering focus Strong experience designing data models and warehouse schemas that support multiple teams Proven experience building and operating production ETL/ELT pipelines, including orchestration, testing and monitoring Expert-level SQL and strong Python skills Hands-on experience with a modern data warehouse or query engine such as ClickHouse, Athena, Snowflake, BigQuery, Redshift or similar Experience with BI and reporting tools such as Metabase, Looker, Tableau or similar Experience defining business metrics and building reporting infrastructure that drives decision-making Experience working with event data at scale, ideally from connected devices, consumer products or technology platforms Degree in Computer Science, Engineering, Statistics or a related discipline, or equivalent practical experience Willingness to work from the Winnipeg office three days per week Nice to Have Experience with product analytics, experimentation, funnel analysis and retention metrics Experience with complex measurement, attribution or analytics systems Experience building evaluation pipelines or ground truth datasets for machine learning models Previous experience helping establish or grow a data team Familiarity with AWS data services and dbt or a similar transformation framework Why Join? This is an opportunity to join a fast-growing, VC-backed technology business at an exciting stage of its development. With an established technology platform, a growing connected-device network and increasingly sophisticated AI capabilities, data is becoming central to how the business operates and scales. You'll have the opportunity to take ownership of the data function, make important architectural decisions and build infrastructure that will influence everything from product analytics to machine learning evaluation and business intelligence. Rather than stepping into an established data environment and maintaining existing systems, you'll have the autonomy to shape how data engineering evolves within the business, working closely with engineering leadership and having a tangible impact from day one. If you're a hands-on Data Engineer who enjoys building scalable data infrastructure, solving complex problems and having real ownership, this is an opportunity worth exploring. Interested in learning more? Apply today.

What you’ll do

Design and standardize data models, own production ETL/ELT pipelines and the data warehouse, and build reporting infrastructure, dashboards, and business metrics. Partner with engineering and other teams to improve data collection and establish scalable foundations for operational reporting, product analytics, and machine learning evaluation.

Requirements

Requires at least six years of relevant experience, strong data engineering skills, expert SQL, strong Python, and hands-on experience with modern data warehouses, production pipelines, and BI tools. Candidates should have experience with large-scale event data and business reporting, and be willing to work from the Winnipeg office three days per week; a relevant degree or equivalent practical experience is required.

Benefits

• Competitive Salary
• Employee Stock Options
• Employer-Covered Health Benefits
• Gym Membership
• Catered Lunches
• Unlimited Paid Vacation
• Flexible Working Hours
• Hybrid Working
• Dog-Friendly Office
• Free On-Site Parking
• Relocation Support

Listed skills

• SQL · Preferred
• Python · Preferred
• Reporting · Preferred
• Amazon Web Services · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Engineering
• Data Modeling
• Data Warehousing
• ETL/ELT Pipelines
• SQL
• Python
• Pipeline Orchestration
• Pipeline Testing
• Pipeline Monitoring
• Business Intelligence
• Reporting
• Business Metrics
• Event Data
• Product Analytics
• Machine Learning Evaluation
• AWS

Job areas

• Data & Analytics
• Technology
• Software
• Engineering