Data Engineer – Banking / Financial Domain

Staffingine LLC; Toronto; On-site; CAD 90,000 - 130,000; Full time

Job summary

Staffingine LLC in Toronto, ON is seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines for reporting and analytics. The role emphasizes Databricks, Azure databases, Oracle, and Python to deliver robust data solutions onsite.

You will collaborate with analysts and engineers, implement data quality checks, and optimize processing performance while adhering to security and governance practices. This is an onsite role with an in-person interview requirement.

Qualifications

• 5–7 years of experience in data engineering or data development.
• Proficiency with Databricks, Python and SQL for data processing.
• Experience with ETL/ELT, data integration, and data transformation.
• Experience with Azure database technologies and Oracle Database.

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.

Skills

Python programming

Data pipelines

SQL querying

ETL/ELT

Troubleshooting

Collaboration

Data quality

Education

Bachelor's degree in a relevant field

Tools

Databricks

Azure databases

Oracle Database

Python

SQL

Delta Lake

Spark

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.