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About the Role

We’re looking for a Master Data Management (MDM) Engineer to support and evolve our Enterprise Data Platform. This role combines data stewardship, MDM operations, and modern data engineering, with a focus on ETL/ELT pipelines, Snowflake-based processing, and data quality management. You will play a key role in ensuring trusted Customer & Contact data (Golden Records) while driving automation, intelligent monitoring, and continuous improvement across the data platform.

Responsibilities

Design, build, and maintain ETL/ELT pipelines to ingest data into Snowflake and MDM.
Develop SQL-based transformations for standardization, cleansing, and enrichment.
Implement data models (staging, curated, golden layers) aligned with MDM architecture.
Optimize Snowflake performance, storage, and cost efficiency.
Implement data validation, reconciliation, and monitoring frameworks across pipelines.
Define and implement data quality rules, checks, and KPIs.
Perform root cause analysis and implement preventive fixes.
Support QA/UAT testing for enhancements, fixes, and data remediation.
Identify and implement automation opportunities across MDM and data pipelines.
Drive adoption of AI-driven automation and intelligent workflows to reduce manual effort.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or related field.
3+ years of experience in MDM, data engineering, or data stewardship roles.
Strong understanding of MDM concepts (Customer, Contact, Match/Merge, Golden Record).
Strong understanding of data quality and governance principles.
Hands-on experience with SQL and relational databases.
Experience working with ETL/ELT pipelines and data flows.
Experience with Reltio/ Semarchy xDM (or similar MDM tools).
Strong experience with Snowflake: SQL optimization, data modeling, ELT pipelines.
Hands-on experience with ETL tools: Talend / Qlik / Informatica / AWS Glue.
Familiarity with AWS (S3, Glue, Lambda).
Exposure to DevOps tools (JIRA, Git, Jenkins).
Familiarity with AI-assisted data operations, anomaly detection, or automation frameworks is a plus.

Skills

MDM
Data Engineering
Data Stewardship
ETL/ELT pipelines
Snowflake
Data Quality Management
SQL
Relational Databases
Reltio/ Semarchy xDM
Talend / Qlik / Informatica / AWS Glue
AWS (S3, Glue, Lambda)
DevOps tools (JIRA, Git, Jenkins)
AI-assisted data operations
Anomaly detection
Automation frameworks

Location

1 Adelaide in Toronto, Ontario

Work Type

Full-time

Experience Level

3+ years of experience

Education Level

Bachelor’s degree in Computer Science, Information Systems, or related field.

Salary/Compensations

$62,600-$86,000 annually

Benefits

Comprehensive health and welfare benefits
Paid time-off programs (vacation, sick leave, and holidays)

About the Company

Element employees make a difference in the lives of others every day.
We are re-defining the fleet management industry to be people first, then business – delivering on our promise of a superior client experience.
This takes hard work and innovation, and we need more like-minded people on our team.

Equal Opportunity

Element Fleet Management and its wholly owned subsidiaries are an equal opportunity employer committed to diversity, equity, inclusion, and belonging.
We are pleased to consider all qualified applicants for employment without regard to race, color, religion, genetic information, sex, gender identity, sexual orientation, age, marital status, family status, ancestry, national origin, citizenship, physical or mental disability, veteran status, military obligations or any other characteristic protected by federal, state and local laws.
Disability-related accommodations during the application and interview process are available upon request.
Should you require an accommodation with our hiring process please send an email to talentacquisition@elementcorp.com or call (800) 665-9744.
Element Fleet Management also uses AI-assisted tools to help screen and assess applications.
These tools analyze information you provide (for example, your rēsumē and screening responses) to identify job-related skills, qualifications, and experience.
AI outputs do not by themselves determine whether you advance or receive an offer – they assist recruiters and hiring managers.
Final hiring decisions are made by people.