Senior Software Engineering Manager - Pyspark, SQL & AI
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 23h ago
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Job Location
Jersey City, NJ, United States
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
This role is for a Senior Software Engineering Manager within the Corporate Technology, Asset & Wealth Management Finance team. You will lead multiple engineering teams responsible for delivering data engineering and business intelligence solutions that support finance stakeholders. Your focus will be on setting clear technical direction, establishing operating practices, and defining delivery expectations across teams, ensuring a balance between speed, quality, and operational excellence. You will collaborate closely with business and technology leaders to prioritize outcomes and align roadmaps, fostering an inclusive culture centered on ownership, continuous improvement, and the responsible application of enterprise-authorized AI capabilities. This is an opportunity to combine people leadership with technical depth and achieve measurable impact.
Responsibilities
- Lead multiple teams in delivering data engineering platforms and analytics solutions aligned with finance priorities.
- Define and execute the data engineering roadmap, including the design and modernization of scalable pipelines.
- Architect and guide PySpark-based processing patterns to enhance performance, reliability, and maintainability.
- Deliver business intelligence capabilities by partnering with stakeholders to define requirements and drive adoption.
- Establish engineering standards for code quality, testing, documentation, and production readiness.
- Drive operational excellence through service health monitoring, incident reduction, and improved recoverability.
- Develop talent via coaching, feedback, hiring, and succession planning.
- Partner with risk, security, and governance stakeholders to ensure appropriate handling of sensitive data.
- Scale operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes.
- Apply knowledge of Software Development Life Cycle tools, including enterprise-authorized AI-assisted development and automation, to drive efficiency and support capacity unlock initiatives.
Requirements
- Demonstrated people leadership experience managing multiple engineering teams and leaders.
- Hands-on knowledge of data engineering concepts, including batch processing patterns and data pipeline design.
- Hands-on experience building or supporting PySpark-based solutions in production environments.
- Experience delivering business intelligence solutions using business intelligence tools.
- Strong ability to translate business outcomes into actionable engineering roadmaps and delivery plans.
- Strong understanding of software engineering fundamentals, including code quality, testing, and production support.
- Effective stakeholder management skills, including influencing across technology and business partners.
- Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance, measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations.