Data Engineer

The Data Engineer role requires mid-level experience with a strong foundation in Python programming and expertise in designing and implementing data processing workflows and ETL pipelines, particularly within the Databricks analytics platform. Candidates should have proficiency in writing and optimizing complex queries, demonstrating a solid understanding of data architecture principles. Experience with big data processing frameworks, especially Apache Spark, is essential. Familiarity with version control systems like git and Infrastructure as Code (IaC) tools such as Terraform, Pulumi, or Databricks Asset Bundles is important, alongside knowledge of CI/CD practices to ensure streamlined deployment and integration processes. The role involves close collaboration with data engineers, analysts, and business stakeholders to translate requirements into strategic, scalable data solutions, contributing to the bank's Core Payments Platform. Staying current with advancements in data engineering and big data technologies is expected to continually enhance methodologies and solutions. While experience with Databricks is a preferred asset, the primary focus is on the ability to create reusable templates and frameworks that can be adopted across multiple domains, highlighting the candidate’s capacity for innovation and leadership in data platform development. A bachelor’s degree supports the technical foundation necessary for this position, which emphasizes practical skills and hands-on experience in a high-priority financial services environment.