Data Engineer
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- 5–7 years of experience in data engineering or data development.
- Posting language
- English
- Posted
Original job description
Staffingine LLC is excited to announce an excellent Contract opportunity with one of our top clients!
Job Title: Data Engineer
Location: Toronto, ON
Hire Mode: Contract or Fulltime
Domain: Banking / Financial Must
Ideal Candidate Profile: A hands-on Data Engineer with strong Databricks, Python, Azure database, and Oracle experience. AI experience will be an added advantage.
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.
More about this job
Responsibilities
Design, develop, and maintain scalable data pipelines and workflows for data ingestion, transformation, integration, reporting, and analytics using Databricks, Python, SQL, Azure databases, and Oracle. Ensure data quality and security, optimize performance, troubleshoot pipeline issues, collaborate with business and engineering teams, and support AI or machine learning data solutions where applicable.
Requirements
Requires 5–7 years of data engineering or data development experience, with hands-on expertise in Databricks, Azure database technologies, Oracle, SQL, and Python. Candidates should also have ETL/ELT and data integration experience, strong analytical and troubleshooting skills, and good communication and collaboration skills; AI or machine learning exposure is preferred.
Skills
- Databricks
- Python
- Azure Database Technologies
- Oracle Database
- SQL
- ETL/ELT
- Data Integration
- Data Transformation
- Data Pipelines
- Data Quality
- Spark
- PySpark
- Delta Lake
- Azure Data Services
- Data Security
- Performance Optimization
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- Data Engineering
- Databricks
- Python
- Azure Database Technologies
- Oracle Database
- SQL
- ETL/ELT
- Data Pipelines
- Data Ingestion
- Data Transformation
- Data Integration
- Data Processing
- Data Cleansing
- Data Validation
- Data Quality
- Business Reporting
- Analytics
- Spark
- PySpark
- Delta Lake
- Azure Data Services
- Artificial Intelligence
- Machine Learning
- Data Security
- Data Governance
- Performance Optimization
- Banking
- Financial Services