Senior Data Engineer
About The Position
At BC Ferries, data is becoming a critical driver of how we operate, serve our customers, and make informed business decisions. As we continue to modernize our technology landscape, we're investing in an enterprise data platform that will power reporting, analytics, artificial intelligence, and operational decision-making across one of British Columbia's most essential transportation networks. We're looking for a Senior Data Engineer to help build that foundation. In this role, you'll design and deliver scalable, production-grade data pipelines and enterprise data products that enable trusted insights across the organization. Working with modern cloud technologies and collaborating with data engineers, analytics engineers, data governance specialists, and business leaders, you'll help transform complex data into reliable, secure, and high-performing information that supports everything from operational efficiency and asset management to customer experience and strategic planning. If you're passionate about solving complex data challenges, building robust data platforms, and creating solutions that have enterprise-wide impact, we'd love to hear from you.
Requirements
- A bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Data Analytics, Business Technology, or a related discipline (a master's degree is an asset)
- A minimum of 5-8 years of hands-on experience designing, developing, and supporting enterprise data platforms and modern data solutions
- Strong expertise developing scalable data pipelines using SQL, Python, and PySpark
- Experience with cloud-based data platforms, modern data architectures, and enterprise data engineering practices
- Strong knowledge of dimensional data modelling, data warehousing, and data transformation techniques
- Experience implementing data governance, security, lineage, and data quality controls
- Familiarity with software engineering practices including Git, CI/CD, automated testing, and code reviews
- Excellent analytical, problem-solving, and communication skills, with the ability to work effectively across technical and business teams
Responsibilities
- Designing, building, and maintaining complex, production-grade data pipelines and transformations across Bronze, Silver, and Gold layers, ensuring reliable integration, monitoring, performance optimization, and reusable enterprise data products
- Designing and maintaining robust Data Lakehouse data models, dimensional models, and transformation patterns that prepare standardized, analytics-ready data for reporting, enterprise data products, and semantic consumption
- Building and delivering trusted, reusable Gold-layer data products aligned with enterprise data standards, governance requirements, reporting needs, and approved business use cases
- Implementing and maintaining data governance, data quality controls, validation rules, reconciliation processes, and conformance checks to ensure enterprise data is accurate, reliable, secure, and auditable
- Optimizing data models, pipelines, transformations, and processing patterns to maximize performance, scalability, operational reliability, security, and cloud cost efficiency (FinOps)
- Designing and implementing secure data models and transformation processes that embed enterprise access controls, data classifications, governance policies, lineage, and auditability requirements
- Collaborating with Platform Data Engineers, Analytics Engineers, Data Governance partners, and business stakeholders to develop scalable, secure, and high-performing data solutions that meet business and technical requirements
- Leading the troubleshooting, root cause analysis, and resolution of complex pipeline failures, transformation issues, data quality concerns, and production support incidents
- Maintaining technical metadata, data lineage, documentation, source-to-target mappings, coding standards, and reusable engineering practices to ensure enterprise data assets remain understandable, discoverable, and maintainable
- Applying software engineering best practices, including version control, code reviews, automated testing, CI/CD, release management, platform modernization, and technical debt reduction to continuously improve the enterprise data platform
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What This Job Offers
Job Type
Full-time
Career Level
Senior
