About the job
COMPANY OVERVIEW
KKR & Co. Inc. is a premier global investment firm specializing in alternative asset management as well as capital markets and insurance solutions. With a commitment to delivering attractive investment returns through a disciplined and patient approach, KKR is dedicated to fostering growth in its portfolio companies and communities. The firm manages investment funds that invest in private equity, credit, and real assets, and collaborates with strategic partners that oversee hedge funds. KKR’s insurance subsidiaries provide retirement, life, and reinsurance solutions under the auspices of Global Atlantic Financial Group.
TEAM OVERVIEW
The ADAPT (AI, Data, and Platform Technologies) Engineering team plays a critical role in KKR's technological vision, focusing on the architecture and support of the firm’s core data and AI capabilities. This team is recognized for its significant contribution to global scale and business transformation, driving technological excellence through the development of robust, platform-based solutions that enhance agility and deliver tangible business outcomes.
POSITION SUMMARY
We are seeking a skilled Lead Data Engineer to join the core ADAPT Engineering team. This hands-on role requires deep expertise in modern data engineering and the ability to derive actionable insights from complex, large-scale financial datasets. The ideal candidate will be pivotal in designing and implementing state-of-the-art data engineering capabilities that streamline the processing of vast data pipelines, utilize advanced AI-driven insights, and ensure seamless integration across diverse cloud-based databases.
The successful applicant will define the technical architecture for KKR's data structuring, storage, and utilization, optimizing data integrity, performance, and accessibility for essential firm-wide services.
KEY RESPONSIBILITIES
- Establish and lead the enterprise strategy and target-state architecture for Data Explorer, ensuring scalable, governed, and user-friendly data discovery, access, sharing, and reuse across the organization.
- Develop the long-term vision, design principles, and adoption framework for enterprise data exchange capabilities, encompassing metadata, semantic consistency, entitlements, lineage, interoperability, and trusted data product consumption.
- Serve as the senior technical authority for data analyst agents, guiding the development of agentic capabilities.

