Data Engineer – Banking / Financial Domain
- Toronto, ON, Canada
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Original job description
Job Title: Data Engineer – Banking / Financial Domain
Location: Toronto, ON (onsite) -
In-person Interview is must
Experience: 5–7 Years
Open to Contract & Fulltime
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.
More about this job
Responsibilities
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 while following security, governance, and documentation practices.
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 have experience with ETL/ELT, data integration and transformation, and strong analytical and communication skills; exposure to AI or machine learning is an advantage.
Skills
- Databricks
- Azure Database Technologies
- Oracle Database
- SQL
- Python
- ETL/ELT
- Data Integration
- Data Transformation
- Data Pipelines
- Data Quality
- Spark
- PySpark
- Delta Lake
- Data Security
- Data Governance
- Machine Learning
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- Data Engineering
- Banking
- Financial Services
- Databricks
- Azure Database Technologies
- Oracle Database
- Python
- SQL
- ETL/ELT
- Data Pipelines
- Data Ingestion
- Data Transformation
- Data Integration
- Data Processing
- Business Reporting
- Analytics
- Data Cleansing
- Data Validation
- Data Quality
- Performance Optimization
- Data Security
- Data Governance
- Spark
- PySpark
- Delta Lake
- Azure Data Services
- Artificial Intelligence
- Machine Learning