Data Engineer (Databricks, Python, Pyspark and SQL)- 12 + Years Experience MUST

Role: Data Engineer (Databricks, Python, Pyspark and SQL) Long Term Contract Mississauga, ON- 3 Days a week Onsite MUST Interview Process: Online Assessment Coding Test, 2 In-Person Round of Interviews 1 Professional Reference MUST Key Responsibilities: Design, develop, and maintain scalable and efficient data pipelines using Databricks, Python, Pyspark, and SQL. Write optimized and complex SQL queries to extract, transform, and load data. Develop and implement data models, schemas, and architecture that support banking domain requirements. Collaborate with data analysts, data scientists, and business stakeholders to gather data requirements. Automate data workflows and ensure data quality, accuracy, and integrity. Manage and coordinate release processes for data pipelines and analytics solutions. Monitor, troubleshoot, and optimize the performance of data systems. Ensure compliance with data governance, security, and privacy standards within the banking domain. Maintain documentation of data architecture, pipelines, and processes. Stay updated with the latest industry trends and incorporate best practices. Required Skills and Experience: Proven experience as a Data Engineer or in a similar role with a focus on Databricks, Python, Pyspark, and SQL. Strong understanding of data warehousing concepts and cloud data platforms, especially Snowflake. Hands-on experience with release management, deployment, and version control practices. Solid understanding of banking and financial services industry data and compliance requirements. Proficiency in Python scripting and Pyspark for data processing and automation. Experience with ETL/ELT processes and tools. Knowledge of data governance, security, and privacy standards. Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Preferred Qualifications: Good Knowledge in Azure and Databricks in highly preferred. Knowledge of Apache Kafka or other streaming technologies. Familiarity with DevOps practices and CI/CD pipelines. Prior experience working in the banking or financial services industry.

Design, develop, and maintain scalable data pipelines and optimized SQL queries to support banking domain requirements. Automate data workflows while ensuring data quality, security, and compliance with governance standards.

Requires over 12 years of experience with expertise in Databricks, Python, PySpark, and SQL. Candidates should have a strong background in the banking and financial services industry and experience with cloud data platforms like Snowflake.

• Microsoft AzureSouhaitée
• SQLSouhaitée
• CI/CDSouhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Databricks
• Python
• PySpark
• SQL
• Snowflake
• ETL/ELT
• Data Modeling
• Data Warehousing
• Azure
• Apache Kafka
• DevOps
• CI/CD
• Release Management
• Data Governance
• Version Control
• Banking Domain Knowledge

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

Expérience minimale

10+ ans

Postuler avant le

2 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Présence au bureau

3 jours par semaine

Niveau d’expérience

Mid-Senior level

Mode de candidature

La candidature directe est offerte