The Data Development team's mission is to support Seaspan's growth by delivering trustworthy, scalable, and user-friendly data solutions for analytics, reporting, machine learning, and data-driven applications.
As Team Lead, Data Engineering, you will be a hands-on technical and people leader responsible for the day-to-day direction of the Data Engineering team. You will directly manage Data Engineers while remaining actively involved in solution design, development, code review, troubleshooting, and delivery using Databricks and Azure technologies.
You will balance team leadership with hands-on engineering to deliver reliable data pipelines, Lakehouse architecture, reusable data models, and enterprise data products. You will set priorities, assign work, coach team members, support performance and development discussions, remove delivery obstacles, and promote consistent engineering practices.
You will also collaborate with business stakeholders, Data Architects, Data Scientists, Analysts, application teams, Data Governance, and Cybersecurity. Success in this role requires strong technical judgment, problem-solving, communication, stakeholder management, documentation, and the ability to influence technical decisions and deliver through others.
Job Responsibilities:- Lead and directly manage Data Engineers.
- Remain hands-on in solution design, development, code review, testing, troubleshooting, deployment, and production support.
- Set technical direction and delivery priorities for the team.
- Design, develop, and maintain scalable data solutions using Azure Databricks, Delta Lake, Unity Catalog, and Azure data services.
- Build and optimize batch and real-time data pipelines.
- Develop enterprise Lakehouse solutions and reusable dimensional data models that support reporting, analytics, machine learning, AI.
- Develop robust ETL/ELT integrations across enterprise applications, APIs, databases, SaaS platforms, files, and external partners.
- Support Data Operations Team for the resolution of data quality, integration, pipeline, and performance issues, including critical production incidents.
- Apply data governance, lineage, cataloging, metadata, security, privacy, and access-control standards in partnership with Architecture, Data Governance, and Cybersecurity.
- Establish and enforce engineering standards for version control, automated testing, code quality, deployment, CI/CD, documentation, and supportability.
- Translate business requirements into practical technical designs, delivery plans, and integrated data solutions.
- Coordinate team delivery with Data Analysts, Data Scientists, Architects, application teams, vendors, and business stakeholders.
- Support secure enterprise data sharing and external data exchange solutions.
- Contribute to solution reviews, roadmap planning, capacity planning, technology evaluations, and the evolution of Seaspan's enterprise data architecture.
Qualifications and Experience:- Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related discipline, or equivalent practical experience.
- At least 7 years of experience in data engineering, data integration, or data platform development, including 3 years of hands-on experience with Azure Databricks or a comparable cloud data platform.
- Experience designing and delivering enterprise-scale data lakes, data warehouses, or lakehouse architectures and leading data modernization initiatives.
- Demonstrated experience leading Data Engineers, including assigning work, reviewing technical delivery, coaching team members, and supporting performance and career development.
- Strong Python and SQL skills, including development of scalable ETL/ELT pipelines and processing of large datasets.
- Strong knowledge of data modeling, dimensional modeling, and data warehouse design principles.
- Working knowledge of data governance, data quality, metadata management, lineage, security, and access control.
- Experience with Git, Azure DevOps, CI/CD pipelines, automated testing, and Infrastructure-as-Code practices.
- Experience integrating REST APIs, MCP connectors, file-based interfaces, SaaS platforms, and external data-sharing solutions.
- Relevant Azure data engineering or Databricks Certified Data Engineer Associate or Professional certification is a plus.
- Experience with machine learning platforms, MLOps, streaming technologies, or real-time analytics.
- Experience modernizing legacy data warehouse environments to cloud lakehouse architectures.
- Experience in maritime, logistics, transportation, or industrial environments is an asset.
Additional Qualifications:- Periodic overtime may be required to support project deadlines, production deployments, or global stakeholder engagement.
- Participation in after-hours support during critical incidents or platform upgrades may be required.
Compensation and Benefits Package:Seaspan's total compensation is based on our pay-for-performance philosophy that rewards team members who deliver on and demonstrate our high-performance culture. The hiring range for this position is $120,000 - $130,000 CAD per annum. The exact base salary offered will be commensurate with the incumbent's experience, job-related skills and knowledge, and internal pay equity.
A WEEK AT SEA WITH SEASPANThis video was taken on board our 4250 TEU vessel, Seaspan Santos, during a six-day passage in September 2013.
JOIN THE BEST AT SEAWhen you join the Seaspan family, you become a part of a company with one of the newest and most advanced fleets in the industry. Our modern vessels are maintained to the highest standards and offer excellent living conditions for our seafarers.
