Lead Data Engineer

MTN Industrial

. Manage, coach and develop the data engineer on the team .

Posted 10/31/2026full-timeRemote • CanadaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in data engineering with a focus on managing production data platforms, building reliable data pipelines, and leveraging AI tools for efficiency. Proven ability to lead and develop teams while ensuring compliance with data governance and privacy standards.

Highest-signal resume keywords

Databricks Lakehouse ManagementData Pipeline DevelopmentSQL ProficiencyPython ProgrammingTeam Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData Pipeline BuildingSQLPythonAI Tool UtilizationData GovernanceData ManagementData Quality AssuranceData ModelingData Ingestion

Soft Skills

CoachingMentoringCollaborationAutonomyProblem-Solving

Tools & Technologies

DatabricksSalesforceNetSuiteSigmaJiraGitHub

Industry Keywords

FintechPaymentsRegulated EnvironmentsEmbedded AnalyticsData PrivacyGDPRPII HandlingAccess Control

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Manage, coach and develop the data engineer on the team
Set standards for code review, testing, documentation and data on-call
Plan team work with Engineering, Finance and Product
Help shape and grow the team, including hiring when needed
Own the Databricks lakehouse end to end, including ingestion, modelling, quality and cost
Build and run pipelines from the production platform, Salesforce, NetSuite and third-party sources
Maintain accurate, fast and self-serve internal reporting in Sigma
Make pipelines observable and recoverable
Run data supporting month-end close, revenue calculations and vendor cost reconciliation
Support audits and year-end reconciliation
Build and improve customer-facing data products, including data connectors and embedded reporting
Partner with Engineering and Product on fraud and risk data features
Build data foundations for safe use by AI tools and agents
Use AI to build, test and document pipelines faster
Identify and support product and team improvements using data and AI
Bring Jira and GitHub data into the warehouse to measure engineering delivery
Apply data management and privacy policies
Partner 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
Preferred: Formal people management, and interest in growing a team over time
Preferred: Fintech, payments or other regulated environments
Preferred: Customer-facing data products, embedded analytics or data sharing
Preferred: Building context layers, retrieval or data pipelines for AI agents
Preferred: 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
Diverse team working together on a common mission