Lead Data Engineer

MTN Industrial

. Manage, coach and develop the data engineer on your team, with regular one to ones and clear goals .

Posted 10/31/2026full-timeRemote • CanadaSenior💰 CA$155,000 - CA$166,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing and developing data engineering teams while owning end-to-end data platforms, including Databricks. Proficient in building reliable data pipelines, applying data governance, and leveraging AI tools to enhance workflows and product offerings.

Highest-signal resume keywords

Data Engineering LeadershipDatabricks Lakehouse ManagementPipeline Development with SQL and PythonData Governance and Privacy ComplianceCustomer-Facing Data Products

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringDatabricksSQLPythonPipeline DevelopmentData GovernanceAI ToolsData ModellingData Quality ManagementData Ingestion

Soft Skills

Team ManagementCoachingMentoringAutonomyCollaboration

Tools & Technologies

SalesforceNetSuiteSigmaJiraGitHub

Industry Keywords

FintechPaymentsRegulated EnvironmentsGDPRPII Handling

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Manage, coach and develop the data engineer on your team, with regular one to ones and clear goals
Set standards for code review, testing, documentation and data on-call
Plan the team's work with Engineering, Finance and Product
Help shape the team as it grows, including hiring
Own Trolley's Databricks lakehouse end to end: ingestion, modelling, quality and cost
Build and run pipelines from the production platform, Salesforce, NetSuite and third-party sources
Keep internal reporting in Sigma accurate, fast and self-serve
Make pipelines observable and recoverable
Run data behind month-end close, revenue calculations and vendor cost reconciliation
Support audits and year-end reconciliation
Build and improve customer-facing data products, including the data connector and embedded reporting
Work on data features such as fraud and risk signals
Build data foundations for safe AI tools and agents
Use AI to build, test and document pipelines faster
Identify and evidence opportunities for data and AI to improve the product and team workflows
Bring Jira and GitHub data into the warehouse to measure engineering delivery
Apply data management and privacy policies, partnering with InfoSec and Compliance on access, retention and audit requirements

Requirements

What you’ll need

7+ years in data engineering, with ownership of a production data platform
Experience leading other engineers: managing, mentoring or leading a small team day to day
Deep experience with Databricks or a similar lakehouse, SQL, and Python
Experience building reliable pipelines from operational databases and SaaS systems
Experience supporting finance or accounting processes with data
Hands-on use of AI tools in your own engineering work, and clear thinking about where AI helps and where it doesn't
Comfortable as the most senior data person in the company, with a lot of autonomy
Formal people management, and interest in growing a team over time
Fintech, payments or other regulated environments
Customer-facing data products, embedded analytics or data sharing
Building context layers, retrieval or data pipelines for AI agents
Data governance and privacy in practice: PII handling, access control, GDPR

Benefits

Comp & perks

Competitive salary
ESOP Program: Meaningful equity and ownership that aligns your success with ours
Extended healthcare benefits from Day 1
4 weeks paid vacation per year + public holidays (+ 1 extra vacation day per year of service)
30 days remote work from anywhere
Gym membership allowance
1/2 day Fridays off during summer
Company-provided use of Apple MacBook and Mac gear
Join an amazing team of diverse people working together on a common mission