Data Engineer – Snowflake, Azure & Databricks
Experience: Minimum 3 years Employment Type: Contract Job Category: Information Technology / Data Engineering
Job Overview
We are seeking a skilled and motivated Data Engineer with a minimum of 3 years of hands-on experience in Snowflake, Microsoft Azure, Azure Databricks, Python, PySpark, Apache Spark, and SQL.
The successful candidate will be responsible for designing, developing, optimizing, and maintaining scalable data pipelines, ETL/ELT workflows, and cloud-based data platforms to support enterprise analytics, reporting, and business intelligence.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Azure Data Factory (ADF), Azure Databricks, and Snowflake.
- Develop and optimize data transformation processes using Python, PySpark, Apache Spark, and SQL.
- Build and maintain cloud-based data warehouses using Snowflake.
- Integrate data from multiple sources, including relational databases, APIs, flat files, and cloud storage.
- Implement data ingestion, cleansing, transformation, and validation processes.
- Develop complex SQL queries, stored procedures, views, and data models.
- Work with Azure Data Lake Storage (ADLS Gen2), Azure Blob Storage, and other Azure cloud services.
- Perform performance tuning and optimization of Snowflake queries, Spark jobs, and data pipelines.
- Implement data quality checks, error handling, monitoring, and troubleshooting.
- Support incremental data loading, change data capture (CDC), and batch processing.
- Collaborate with data analysts, business stakeholders, and development teams to deliver reliable data solutions.
- Maintain technical documentation and follow data engineering best practices.
- Support CI/CD processes, version control, and automated deployments.
Required Qualifications
- Minimum 3 years of professional experience in Data Engineering or a related role.
- Hands-on experience with Snowflake Data Warehouse.
- Strong experience with Microsoft Azure, including Azure Data Factory and Azure Data Lake Storage.
- Practical experience with Azure Databricks and Apache Spark.
- Strong programming skills in Python and PySpark.
- Advanced SQL skills, including complex joins, CTEs, window functions, and query optimization.
- Experience designing and implementing ETL/ELT pipelines.
- Understanding of data warehousing concepts, dimensional modelling, and data integration.
- Experience troubleshooting data pipeline failures and resolving data quality issues.
- Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
- Experience with Snowflake Streams, Tasks, Snowpipe, and stored procedures.
- Knowledge of Delta Lake and the Databricks Lakehouse architecture.
- Experience with Git, Azure DevOps, and CI/CD pipelines.
- Familiarity with REST APIs, JSON, Parquet, and CSV data formats.
- Understanding of cloud security, RBAC, and data governance.
- Experience with Power BI or other business intelligence tools.
- Relevant Snowflake, Microsoft Azure, or Databricks certifications.
Education
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience.
Pay: $25.00-$50.00 per hour
Work Location: Hybrid remote in Oakville, ON
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