Chief Developer in Data Engineering

A career as a Chief  Developer in Data Engineering  within the Data Strategy team in the Business Performance, Evolution and Processes sector at National Bank means acting as an analytical data specialist. Leveraging your expertise in data architecture and modeling, your experience building data pipelines, and your knowledge of cloud environments, you contribute directly to data enablement and the transformation of Operations.

Your role

• Define and evolve the data architecture and data models that support the sector’s analytical needs.
• Design, develop, and maintain robust data pipelines (ETL and ELT) within the Bank’s cloud environments.
• Develop integrations and automations that efficiently connect business applications and data platforms.
• Optimize data processing using SQL and Python to improve solution performance, reliability, and efficiency.
• Implement data quality, governance, and control mechanisms to ensure data integrity.
• Influence the sector’s data strategy and contribute to the evolution of the data infrastructure through engineering and automation best practices.

Your team

The Business Performance, Evolution and Processes Vice-Presidency is made up of specialists who work in an agile, proactive, and collaborative manner to seize opportunities, stay at the forefront of technology, and continuously improve processes.

Within the Business Performance, Evolution and Processes sector, you will be part of the Data Strategy team, responsible for driving Operations’ enterprise-wide transformation, and you will report to the Director of Analytics. You will work closely with passionate data experts to accelerate the delivery of our strategic initiatives.

Our team stands out through its data engineering expertise, collaborative mindset, and commitment to high-quality delivery. We aim to provide maximum flexibility to support your quality of life through a hybrid work environment and a flexible, adaptable schedule.

The Bank values continuous development and internal mobility. Our personalized training programs, based on learning through action, enable you to master your profession and develop new areas of expertise. Tools such as the Data Academy, language training, the Harvard Learning Center, as well as coaching and mentoring opportunities are always available to you.

Requirements

• Bachelor’s degree in a related field and five years of relevant experience, or a master’s degree in a related discipline and three years of relevant experience.
• Strong experience in data engineering, including ETL and ELT pipeline development, large-scale data management, data modeling (Data Vault and dimensional modeling), and data architecture.
• Proficiency in SQL and Python for data transformation, integration, and analytics.
• Experience with cloud environments and modern data platforms, including AWS, Snowflake, Terraform, as well as Git, GitHub Actions, Bitbucket, and Jira.
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• Knowledge of software development best practices, automated testing, and continuous integration and continuous delivery (CI/CD) methodologies.
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• Strong analytical thinking, autonomy, proactivity, collaboration and influencing skills, as well as the ability to solve complex problems in a fast-paced and evolving agile environment.