Sr Staff Data Engineer

Lead complex data engineering projects, ensuring they meet business objectives and deliver actionable insights. Develop advanced data architectures and pipelines to analyze large datasets and solve complex business problems. Collaborate with senior leadership to identify data-driven opportunities for business growth and efficiency. Implement best practices for data management, analysis, and visualization. Ensure data governance and compliance with relevant regulations and standards. Provide mentorship and technical guidance to the data engineering team. Must be a self-starter, work independently or as a team member. Proactively remove obstacles to ensure timely delivery of product and goals Write clean and solid code that scales over PB of data and enforce engineering excellence in the organization Improve data management efficiency through AI capabilities, better process and best practices Embed Privacy-by-Design principles into all data solutions and ensure compliance with regulatory requirements. Provide expertise across the data product development lifecycle—spanning data engineering, architecture, and analytics—to design and deliver reusable, accessible, and high-quality data solutions. Design data structures and taxonomies that support standardization, integration, and alignment with business processes. Deliver technical leadership through analytical thinking, innovation, and detailed specifications. Drive data product execution and adoption through a metrics-based approach Strong product sense to identify data challenges and opportunities, and assess the impact of data-driven solutions Leverage enterprise frameworks, governance tools, and reusable architecture patterns for Credit Risk and cross organizations Foster influential cross-functional relationships through collaboration, proactive planning, and decisive leadership to design scalable solutions across platforms and products. 8+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. A CL8 IC is critical to scaling data management capabilities and driving high-impact, cross-functional initiatives that shape the future of data at GCSC Risk. This role provides technical leadership, strategic alignment, and advanced problem-solving at an org-wide level. A multiplier within the organization, a CL8 mentors teams, leads foundational initiatives, and fosters IC communities to scale best practices across GCSC Risk, while also creating a clear career path for individual contributors. They define the technical vision for multiple teams, ensuring alignment with broader business objectives and partnering with business leaders to refine and execute a cohesive data strategy. Their ability to simplify complex problems for a broader audience makes them an invaluable resource in org-wide discussions. A CL8 operates with full autonomy on high-impact, complex technical projects that few others can tackle. To successfully execute on cross-org initiatives that elevate data engineering, we need a T27 who can innovate, drive technical strategy, and ensure that our systems are scalable, efficient, and aligned with GCSC Risk's broader goals. Strong collaboration skills and ability to influence across all organizations and levels within the company Ability to communicate clearly and succinctly to all levels within the organization- translating the organizations goals into execution plans & metrics Possess the ability to connect, engage and lead with empathy Motivate others through a shared vision and confidence that empowers employees and teams to perform at their best Demonstrate ability to delegate work Operate with transparency and honesty in all interactions 12+ years of experience in enterprise data management, with deep expertise across disciplines including data governance, data architecture, and more. Experience with data management and governance tools and technologies Experience with enabling data products within large organizations Proven experience independently developing and implementing recommended approaches to complex/ambiguous problems while making thoughtful trade-offs Deep understanding and hands-on experience in data platforms Strong technical acumen, being able to quickly understand technical details of a product or platform Strong execution skills-ability to deliver results Comfortable working in a fast-paced, results-oriented environment Shows initiative and exhibits a “can-do” attitude Demonstrated willingness to be flexible and adaptable to changing priorities with the ability to motivate in a cross-functional organization Able to see the “big picture”-the end-to-end connection points associated with data and systems Exhibit a passion for Data Management and Analytics Familiarity with AI/ML pipelines or AI-enhanced data systems (data discovery, data quality monitoring, or integrating ML into ETL flows) Passion for bridging the gap between data engineering and machine learning engineering. Experience enabling ML/AI workloads, such as building feature stores, training data pipelines, or model monitoring infrastructure. Experience in financial services, with a strong preference for exposure to the credit risk domain. BS or advanced degree in Engineering, Computer Science, or related technical field.