Data Platform Engineer

Job Title:
Data Platform EngineerLocation:
Edmonton, Alberta (Hybrid)Type:
Permanent Full-Time
All applicants must be legally entitled to work in Canada.
The Position:
Our Edmonton-based client is seeking an experienced Data Platform Engineer to build, operate, and support a modern enterprise data platform. This role works closely with architects, analytics professionals, and business intelligence teams to ensure the organization's data environment is secure, scalable, reliable, and auditable.
The successful candidate will play a key role in data platform operations, security, data quality, testing, monitoring, orchestration, and automation while supporting the delivery of trusted data products across the organization.
What You'll Do:
Data Platform Engineering & Operations
Build, maintain, and support Dev, Test, and Production environments.
Develop and maintain code branching strategies and deployment processes between environments.
Build and support data ingestion, orchestration, and incremental/delta load processes.
Create and maintain CI/CD pipelines to support data platform development and deployment activities.
Contribute to the ongoing modernization of the organization's data platform and retirement of legacy processes.
Establish engineering standards, documentation practices, and operational procedures.
Security, Monitoring & Governance
Implement and maintain platform security controls, including single sign-on (SSO), secrets management, and role-based access controls.
Develop and maintain data quality, testing, and monitoring frameworks.
Implement automated testing, data freshness monitoring, alerting, and operational controls.
Support lineage, documentation, ownership, service level agreements (SLAs), and data governance requirements.
Ensure data products are secure, auditable, and compliant with organizational and regulatory requirements.
Platform Support & Continuous Improvement
Troubleshoot and resolve platform and data pipeline issues.
Conduct root cause analysis and implement preventative measures.
Create and maintain technical documentation, runbooks, and operational procedures.
Collaborate with data, analytics, and business teams to enhance data platform capabilities.
Contribute to platform performance optimization and operational excellence initiatives.
Collaboration & Delivery
Work closely with internal technical and business stakeholders.
Participate in planning, implementation, and continuous improvement initiatives.
Support the delivery of trusted data products used for reporting, analytics, and regulatory requirements.
Contribute to a collaborative, team-oriented environment focused on technical excellence and data reliability.
Mandatories:
Post-secondary education in Computer Science, Engineering, Information Technology, or a related discipline, or equivalent practical experience.
Minimum 5 years of experience in data engineering.
Minimum 2 years of experience building and operating production data pipelines within a modern data platform environment.
Strong Python development skills for data pipelines and automation.
Experience with orchestration tools such as Airflow, Dagster, or similar technologies.
Experience with dbt or comparable data transformation tools.
Strong SQL skills and experience working with relational databases.
Experience with Git, CI/CD pipelines, and software deployment practices.
Experience implementing automated testing and monitoring within production data environments.
Experience implementing security controls including SSO, secrets management, and role-based access management.
Strong experience working with PostgreSQL, including query optimization and performance tuning.
Experience with incremental and delta loading methodologies, including CDC and watermarking approaches.
Experience working with Linux and Docker technologies.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent verbal and written communication skills.
Proven ability to work effectively within collaborative technical teams.
Assets:
CDMP, dbt, or other relevant data engineering certifications.
Experience within highly regulated industries such as insurance or financial services.
Exposure to Guidewire, CDA, or similar industry platforms.
Experience working with multiple ETL tools and database technologies.
Experience with Oracle, SAP BODS, PostgreSQL, or similar enterprise data technologies.
Experience supporting enterprise data modernization initiatives.
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