Data Engineer, Data Platform - Distribution

Careers at KKR•Boston, MA

21h•$180,000 - $210,000•Onsite

About The Position

KKR is seeking a Lead Engineer to join the core ADAPT Engineering team. This is a pivotal, hands-on technical leadership role requiring deep technical expertise in modern data engineering and a proven ability to derive critical insights from complex, large-scale financial data. The successful candidate will be instrumental in designing and constructing world-class data engineering capabilities that efficiently process massive data pipelines, leverage state-of-the-art AI-powered insights and document extraction, and integrate seamlessly across diverse cloud-powered databases. This role requires defining the technical blueprint for how KKR structures, stores, and leverages data to power its AI and investment platforms, ensuring data integrity, performance, and accessibility for critical firm-wide services.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field; advanced degree preferred.
10+ years of experience in data platforms, analytics engineering, enterprise architecture, workflow/process technology, or intelligent automation, with significant experience operating as a senior enterprise technical leader.
Strong ownership mindset, with a proven track record defining and delivering enterprise-scale platform strategy and architecture across multiple domains, with demonstrated success influencing outcomes across large, matrixed organizations.
Deep experience with enterprise data exchange, catalog, marketplace, or self-service data platforms, including metadata strategy, governance, lineage, access controls, interoperability, and adoption at scale.
Demonstrated expertise in AI-enabled analytics and agentic systems, including designing governed, explainable, and auditable patterns for analyst productivity and enterprise decision support.
Strong experience architecting or modernizing business process management (BPM) and workflow orchestration capabilities, with an understanding of how process design, controls, automation, and data platforms must operate together.
Proven success leading BI modernization and rationalization efforts, including platform consolidation, semantic standardization, KPI harmonization, and enterprise reporting transformation.
Strong proficiency in SQL and Python, with broad technical fluency across analytics platforms, data architecture, workflow technologies, and modern integration patterns.
Experience setting architecture direction and technical standards that are adopted across teams, rather than limited to a single application, function, or delivery group.
Demonstrated ability to operate at both strategic and deep technical levels, translating ambiguous business problems into durable platform capabilities and architectural decisions.
Strong executive communication and influencing skills, with the ability to align senior stakeholders, challenge legacy approaches, and drive change across organizational boundaries.
Proven ability to mentor senior talent, shape technical culture, and elevate engineering and architectural rigor across a broad organization.

Responsibilities

Define and drive the enterprise strategy and target-state architecture for Data Explorer as the enterprise data exchange, ensuring scalable, governed, and intuitive data discovery, access, sharing, and reuse across the organization.
Establish the long-term vision, design principles, and adoption model for enterprise data exchange capabilities, including metadata, semantic consistency, entitlements, lineage, interoperability, and trusted data product consumption.
Act as the senior technical authority for data analyst agents, shaping how agentic capabilities are embedded into the analytics ecosystem to improve analyst productivity, decision support, and governed access to enterprise data.
Lead the design and implementation of enterprise data solutions for business analytics, operational workflows, enterprise data sharing, and agent-enabled analytics
Drive reusable architecture and control patterns for workflow orchestration across business domains, enabling scalability, resilience, transparency, and measurable operational improvement.
Own the enterprise roadmap for BI rationalization, defining the target-state reporting and analytics ecosystem and reducing fragmentation across tools, metrics, dashboards, and user experiences.
Lead cross-functional transformation efforts to standardize KPI definitions, semantic layers, reporting patterns, and platform usage models in order to improve consistency, governance, adoption, and cost efficiency.
Partner with senior engineering, architecture, analytics, product, and business leaders to prioritize strategic investments, resolve complex cross-platform issues, and align delivery to the firm’s long-term data and analytics vision.
Mentor senior engineers and technical leaders, raising the standard for architecture quality, platform thinking, and enterprise-scale execution while influencing decisions well beyond immediate team boundaries.
Evaluate emerging technologies and market trends in analytics, workflow automation, agentic systems, and enterprise data platforms, translating them into practical architectural direction and strategic platform investments.
Serve as a trusted advisor on highly complex initiatives, with accountability for shaping decisions that influence multiple platforms, teams, and business functions across the firm.