Lead Software Engineer, Data Engineer

What you'll do

• Develop secure, high-quality production code and perform code reviews and debugging for other team members.
• Design and execute creative software solutions to solve complex technical problems beyond conventional approaches.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
• Establish consistent validation standards for secure coding, peer reviews, and automated testing across the team.
• Apply SDLC toolchain knowledge and automation capabilities to improve the value realized by automated processes.
• Identify and automate the remediation of recurring issues to improve the operational stability of software systems.
• Lead evaluation sessions with external vendors and internal teams to probe architectural designs and technical credentials.
• Coach engineers on the safe, compliant, and responsible use of AI tools within engineering workflows.

What we're looking for

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced proficiency in one or more programming languages including Java, Python, or Scala.
• Good understanding of the AWS platform, including core services, architecture best practices, and security features.
• Extensive experience with big data technologies, including Apache Spark, for large-scale data processing and analytics.
• Demonstrated experience leading the use of approved AI-assisted software development tools and coaching engineers on responsible AI use.
• Proficient in all aspects of the Software Development Life Cycle, including CI/CD, Application Resiliency, and Security.
• In-depth knowledge of the financial services industry and their IT systems with practical cloud native experience.
• Exposure to Databricks (preferred).
• Experience with data visualization and business intelligence platforms (preferred).
• Bachelor's degree in Finance, Technology, Data Science, or a related field (preferred).
• Advanced degree in Finance, Technology, Data Science, or a related field (preferred).