Senior Data Engineer

Job Title:

Senior Data Engineer

Job

Location:

North Vancouver, British Columbia

• Design and implement scalable data architectures and enterprise data products using Azure, Databricks, Delta Lake, Spark/PySpark, SQL, and Python

• Build enterprise-level common entities and reusable datasets serving multiple business domains

• Develop, maintain, and optimize scalable ETL/ELT pipelines and frameworks supporting operational and analytical workloads

• Lead initiatives focused on improving data quality, observability, reliability, and trust across enterprise datasets

• Support implementation of the DCE Data Quality Framework, including automated validation, monitoring, and alerting

• Establish and improve metadata, lineage, governance, and discoverability standards

• Build governed data foundations that enable greater adoption of self-service analytics

• Partner directly with Product Managers and business stakeholders to understand requirements, prioritize initiatives, and deliver high-value data capabilities

• Translate complex business requirements into scalable technical designs and solutions

• Partner with Platform, Architecture, Security, and Governance teams to ensure solutions are scalable, secure, and aligned with enterprise standards

• Lead technical and cross-functional design reviews and contribute to architecture and roadmap planning

• Define and promote CI/CD, testing, source control, infrastructure automation, and deployment best practices

• Mentor junior and intermediate engineers through code reviews, technical design sessions, and hands‑on coaching

• Identify opportunities to improve automation, engineering productivity, platform performance, scalability, reliability, and cost optimization

• Explore emerging technologies and approaches that improve enterprise data delivery and analytics enablement

• 5-8+ years of Data Engineering experience

• Strong experience building cloud-native enterprise data platforms

• Strong Microsoft Azure Data Platform experience

• Advanced hands-on experience with Databricks / Databricks Lakehouse

• Strong Spark / Py Spark experience

• Advanced SQL and Python

• Strong ETL/ELT development and optimization experience

• Experience with Delta Lake

• Enterprise data modeling and dimensional design

• Experience building reusable enterprise data products and data assets

• Data quality monitoring and implementation

• CI/CD and Dev Ops practices

• Source control, automated testing, and deployment methodologies

• Strong understanding of scalable enterprise data architecture

Candidates should have hands-on experience implementing or supporting:

• Data quality frameworks
• Automated data validation and monitoring
• Data observability
• Metadata management
• Data lineage
• Data governance
• Data contracts
• Governed/self-service data access

Salary/Rate: $75.00 per hour