We are seeking a highly skilled and versatile Cloud Data Administrator to join our Data Operations team. Reporting to the Manager, Data Operations, the Cloud Data Administrator plays a key role in the administration and support of our Azure-based data platform, with a particular focus on Databricks, data pipeline orchestration using tools like Azure Data Factory (ADF), and environment management using Unity Catalog. A strong foundation in data engineering, cloud data administration, and data governance is essential.

This is a full-time role located on-site (no remote) in our Vancouver, BC office.

Responsibilities:

Platform Administration and Monitoring:

• Set-up and monitor job pipelines and workflows, troubleshooting failures as necessary to ensure maximum uptime.
• Administer Databricks environments, including user access, clusters, and Unity Catalog for data lineage, governance, and security.
• Support the deployment, scheduling, and monitoring of data workflows and jobs in Databricks and ADF.
• Implement best practices for CI/CD, version control, and operational monitoring for pipeline deployments.
• Implement and manage Delta Lake to ensure reliable, performant, and ACID-compliant data operations.

Security and access management:

• Experience administering secure access to Azure Databricks and related data services using RBAC, managed identities, service principals, and Azure Key Vault
• Understanding of data security, credential management, encryption, secret handling, and least-privilege access principles
• Familiarity with Unity Catalog access controls, data governance, auditing, and compliance best practices

Data Modeling and Integration:

• Design, develop, and optimize scalable data pipelines using Azure Databricks and ADF.
• Collaborate with business and data engineering teams to design data models that support analytics and reporting use cases.
• Support integration of data from multiple sources into the enterprise data lake and data warehouse.
• Configure API calls to utilize our Azure APIM platform.
• Maintain and enhance data quality, structure, and performance within the Lakehouse and warehouse architecture.

Collaboration and Stakeholder Engagement:

• Work cross-functionally with business units, data scientists, BI analysts, and other stakeholders to understand data requirements.
• Translate technical solutions into business-friendly language and deliver clear documentation and training when required.

Required Qualifications:

Apache Spark (on Databricks)

• Proficient in PySpark and spark SQL
• Spark optimization techniques (caching, partitioning, broadcast joins)
• Writing and scheduling notebooks/jobs in Databricks
• Understanding of Delta Lake architecture and features
• Working with Databricks Workflows (pipelines and job orchestration)

SQL/Python Programming

• Handling JSON, XML, and other semi-structured formats
• Experience with API integration using requests, http, etc.
• Error handling and logging API Ingestion
• Designing and implementing ingestion pipelines for RESTful API
• Transforming and loading JSON responses to Spark tables

Cloud & Data Platform Skills

• Databricks on Azure
• Cluster configuration and management
• Unity Catalog features (optional but good to have)

Azure Data Factory

• Creating and managing pipelines for orchestration
• Linked services and datasets for ADLS, Databricks, SQL Server
• Parameterized and dynamic ADF pipelines
• Triggering Databricks notebooks from ADF

Data Engineering Foundations

• Data modeling and warehousing concepts
• ETL/ELT design patterns
• Data validation and quality checks
• Working with structured and semi-structured data (JSON, Parquet, Avro)

DevOps & CI/CD

• Git/GitHub for version control
• CI/CD using Azure DevOps or GitHub Actions for Databricks jobs Infrastructure-as-code (Terraform for Databricks or ADF)

Additional Requirements:

• Bachelor's degree in computer science, information systems, or a related field.
• 4+ years of experience in cloud data engineering, data platform, or analytics engineering role.
• Familiarity with data governance, security principles, and data quality best practices.
• Excellent analytical thinking and problem-solving skills.
• Strong communication skills and ability to work collaboratively with technical and non-technical stakeholders.
• Microsoft certifications in Azure Data Engineer, Power Platform, or related field is desired
• Experience with Azure APIM is nice to have
• Knowledge of enterprise data architecture and data warehouse principles (e.g., dimensional modeling) an asset

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 $100,000 - $115,000 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.