Databricks Developer

We are seeking a skilled Databricks Developer to join our Data Development team. Reporting to the Team Lead, Data Development, the Databricks Developer implements robust data pipelines using Apache Spark on Databricks, supports advanced data transformation, and enables scalable data products that serve enterprise analytics and reporting needs.

Responsibilities

• Design, build, and maintain scalable data pipelines and workflows using Databricks (SQL, PySpark, Delta Lake).
• Develop efficient ETL/ELT pipelines for structured and semi-structured data using Azure Data Factory (ADF) and Databricks notebooks/jobs.
• Integrate and transform large-scale datasets from multiple sources into unified, analytics-ready outputs.
• Optimize Spark jobs and manage Delta Lake performance using techniques such as partitioning, Z-ordering, broadcast joins, and caching.
• Design and implement data ingestion pipelines for RESTful APIs, transforming JSON responses into Spark tables.
• Apply best practices in data modeling and data warehousing concepts.
• Perform data validation and quality checks.
• Work with various data formats, including JSON, Parquet, and Avro.
• Build and manage data orchestration pipelines, including linked services and datasets for ADLS, Databricks, and SQL Server.
• Create parameterized and dynamic ADF pipelines, and trigger Databricks notebooks from ADF.
• Collaborate closely with Data Scientists, Data Analysts, Business Analysts, and Data Architects to deliver trusted, high-quality datasets.
• Contribute to data governance, metadata documentation, and ensure adherence to data quality standards.
• Use version control tools (e.g., Git) and CI/CD pipelines to manage code deployment and workflow changes.
• Develop real-time and batch processing pipelines for streaming data sources such as MQTT, Kafka, and Event Hub.

Job Requirements

• 5+ years of experience in data engineering or big data development.
• Bachelor's degree in computer science or a relevant field, or equivalent training and work experience.
• Strong hands-on experience with Databricks and Apache Spark (PySpark/SQL).
• Proven experience with Azure Data Factory, Azure Data Lake, and related Azure services.
• Experience integrating with APIs using libraries such as requests and
• Deep understanding of Delta Lake architecture, including performance tuning and advanced features.
• Proficiency in SQL and Python for data processing, transformation, and validation.
• Familiarity with data lakehouse architecture and both real-time and batch processing design patterns.
• Comfortable working with Git, DevOps pipelines, and Agile delivery methodologies.
• Experience with dbt, Azure Synapse, or Microsoft Fabric.
• Familiarity with Unity Catalog features in Databricks.
• Relevant certifications such as Azure Data Engineer, Databricks, or similar.
• Understanding of predictive modeling, anomaly detection, or machine learning, particularly with IoT datasets.

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 $95,000 - $110,000 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.

Seaspan Corporation is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, race, colour, religion, gender, sexual orientation, gender identity, national origin, disability, or protected Veteran status.