Data Engineer Databricks

Job summary

Design, develop, and maintain scalable data pipelines and workflows using Databricks, Python, and SQL, integrating data from Azure and Oracle databases. Ensure data quality and performance, troubleshoot pipeline issues, and collaborate with business and engineering teams to deliver secure, governed data solutions for reporting, analytics, and applicable AI or machine learning use cases.

Job details

Job Title: Data Engineer Databricks Location: Toronto, ON Experience: 5–7 Years Job Summary: We are looking for an experienced Data Engineer with strong hands-on expertise in Databricks, Azure database technologies, Oracle, and Python. The ideal candidate should have experience designing, developing, and maintaining scalable data pipelines and data processing solutions to support business reporting, analytics, and data integration requirements. Key Responsibilities: Design, develop, and maintain scalable data pipelines for data ingestion, transformation, and integration. Work extensively with Databricks for data processing, transformation, and analytics. Develop and maintain data workflows using Python and SQL. Integrate data from multiple sources, including Azure databases and Oracle databases. Write optimized queries and implement efficient data transformation logic. Perform data cleansing, validation, and quality checks to ensure accuracy and consistency. Troubleshoot data pipeline failures and resolve performance and data processing issues. Collaborate with business analysts, data architects, and other engineering teams to understand data requirements. Follow best practices for data security, governance, performance optimization, and documentation. Support data solutions involving AI or machine learning where applicable. Required Skills and Qualifications: 5–7 years of experience in data engineering or data development. Strong hands-on experience with Databricks. Experience working with Azure database technologies. Strong experience with Oracle Database and SQL. Proficiency in Python programming for data processing and automation. Experience with ETL/ELT processes, data integration, and data transformation. Strong analytical, troubleshooting, and problem-solving skills. Good communication and collaboration skills. Preferred Skills: Exposure to AI, machine learning, or AI-enabled data solutions. Experience with Spark, PySpark, Delta Lake, or Azure data services. Experience optimizing data pipelines and processing large datasets. Ideal Candidate Profile: A hands-on Data Engineer with strong Databricks, Python, Azure database, and Oracle experience. AI experience will be an added advantage.

What you’ll do

Design, develop, and maintain scalable data pipelines and workflows using Databricks, Python, and SQL, integrating data from Azure and Oracle databases. Ensure data quality and performance, troubleshoot pipeline issues, and collaborate with business and engineering teams to deliver secure, governed data solutions for reporting, analytics, and applicable AI or machine learning use cases.

Requirements

Requires 5–7 years of data engineering or data development experience, with hands-on Databricks expertise and experience in Azure database technologies, Oracle, SQL, and Python. Candidates should have ETL/ELT, data integration, and transformation experience, along with strong analytical, troubleshooting, communication, and collaboration skills; Spark, PySpark, Delta Lake, Azure data services, and AI or machine learning exposure are preferred.

Listed skills

• SQL · Preferred
• Troubleshooting · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Databricks
• Azure Database Technologies
• Oracle Database
• SQL
• Python
• ETL/ELT
• Data Integration
• Data Transformation
• Data Pipeline Development
• Data Quality
• Spark
• PySpark
• Delta Lake
• Azure Data Services
• Performance Optimization
• Troubleshooting

Job areas

• Data & Analytics
• Technology
• Software
• Finance & Accounting

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