Data Architect designing enterprise - level data storage solutions for Servus Credit Union. Collaborating with teams to enhance data practices supporting the organization's goals.
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Data Engineer (Azure Data Factory & Databricks Focus)
Posted via LinkedIn Recruiter (not a company profile)
Posted 3 months ago
About the role
- Data Engineer role focusing on Azure Data Factory & Databricks for building data pipelines. 11-month contract, hybrid work in Oshawa, $90-$95/hour.
Responsibilities
- Design, develop, and productionize modular, scalable ELT/ETL pipelines using Azure Data Factory and Databricks. Build and maintain data lake and data warehouse solutions supporting analytics, applications, and innovation. Cleanse, transform, and optimize large datasets using Python, PySpark, Spark SQL, and SQL. Develop curated, business-centric common data models in collaboration with Data Architects and Data Modelers. Implement data quality, lineage, and governance controls throughout the data lifecycle. Ingest data from multiple sources including CSV, JSON, XML, REST APIs, and enterprise systems. Optimize pipeline performance, reliability, and scalability. Troubleshoot data ingestion, transformation, latency, accuracy, and integrity issues. Collaborate with Business Analysts, Data Scientists, Senior Data Engineers, and Architects. Support BI and analytics use cases, including dimensional modeling and aggregation optimization. Participate in CI/CD pipelines, DevOps workflows, and automated testing strategies. Contribute to metadata management and data cataloging. Provide Tier-2 support for production data pipelines and datasets. Participate in peer code reviews and agile SCRUM ceremonies.
Requirements
- Proven experience building new data pipelines using Azure Data Factory (ADF) for orchestration and Azure Databricks (Spark/PySpark) for transformations. Hands-on expertise with Azure Data Factory and Azure Databricks. Strong programming skills in Python, PySpark, Spark SQL, and SQL. Experience building data lakehouse and data warehouse pipelines. Strong understanding of data structures, data integration patterns, and processing frameworks. Knowledge of data governance, security, and data quality principles. Experience working in an Agile/SCRUM environment. Bachelor's degree in Computer Science, Software Engineering, or related field.
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