Senior Data Engineer

Credigy is seeking a Senior Data Engineer to join our Data and Automation team. This role is responsible for designing, building, and maintaining scalable, reliable data pipelines across both modern cloud platforms and legacy systems. You will own data pipelines end-to-end—from ingestion through consumption—while continuously improving reliability, performance, and scalability.

This is a hands‑on, senior‑level role with a high degree of autonomy. The ideal candidate is comfortable operating in production environments, making architectural decisions, and modernizing existing data systems while continuing to support critical legacy processes.

• Design, build, and maintain end‑to‑end data pipelines, including ingestion, transformation, validation, orchestration, and delivery.
• Develop and optimize data pipelines primarily using Snowflake, SQL Server, and Azure‑based services.
• Ensure data is available, secure, and consistently delivered through a well‑defined and scalable data architecture.
• Assemble large, complex datasets that meet functional and non‑functional business requirements.

• Own the reliability of production data pipelines, including monitoring, troubleshooting, and incident resolution.
• Perform root cause analysis for data issues and implement durable fixes to prevent recurrence.
• Implement and maintain data quality checks and validation frameworks to ensure accuracy and consistency.
• Support multiple teams and systems while maintaining high availability and data integrity.

• Identify and lead opportunities to optimize, automate, and modernize existing data processes and pipelines.
• Maintain and enhance legacy ETL processes, while gradually re‑architecting them toward more scalable, cloud‑native solutions.
• Drive improvements in performance, cost efficiency, and maintainability of the data platform.

• Partner closely with Analytics, Business users, and Data scientist teams to understand data needs and translate them into effective technical solutions.
• Communicate clearly with both technical and non‑technical stakeholders, setting expectations and explaining trade‑offs.
• Contribute to data engineering standards, documentation, and best practices.
• Use Git Hub for version control, code reviews, and collaboration.
• Contribute to and support CI/CD pipelines for data workflows to enable reliable, repeatable deployments.
• Promote engineering best practices, including testing, documentation, and observability.

• 4+ years of experience as a Data Engineer, BI Developer, or ETL Developer.
• Strong SQL expertise with MS SQL Server and T‑SQL.
• Hands‑on experience with SSIS and Azure Data Factory (ADF).
• Experience working with Snowflake and cloud‑based data platforms.
• Proven experience designing, building, and optimizing data pipelines and data architectures.
• Experience supporting production data systems in a fast‑paced environment.
• Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field (or equivalent experience).

• Experience with dbt for data transformation and modeling.
• Experience using Python for data processing and integrations.
• Experience with Informatica.
• Experience implementing CI/CD for data pipelines.
• Strong understanding of data modeling, data quality, and governance best practices.

Founded in 2001, Credigy is a global specialty finance company with flexibility across the capital structure to acquire or finance a broad range of consumer assets. We are a wholly‑owned subsidiary of National Bank of Canada (NBC) and our $9.1B+ portfolio represents 400+ deals and $32B+ in total investments life‑to‑date. We are the partner of choice when financial institutions face complex challenges and strategic changes.

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