Director Of Engineering - ADAPT - Stage

KKR's Gurugram office provides best-in-class business operations services and solutions to our internal stakeholders and clients, drives organization-wide process efficiency and transformation, and reflects KKR's global culture and values of teamwork and innovation. The office contains multifunctional business capabilities and is integral in furthering the growth and transformation of KKR. The office was established with an initial concentration of finance, operations, and technology personnel, followed by the expansion of additional functions and capabilities. KKR’s creation of a Gurugram office builds upon the firm's momentum in India and bolsters its existing presence in Mumbai.

TEAM OVERVIEW

The ADAPT (AI, Data, and Platform Technologies) Engineering team is integral to KKR's technological strategy, architecting, and supporting the firm's foundational data and AI capabilities. This team is recognized as a key enabler for global scale and business transformation, driving excellence by evolving technology into robust, platform-based solutions that enhance agility and deliver material business impact. 

POSITION SUMMARY 

As Director of Engineering, you will be a key member of KKR’s global technology leadership team, reporting to a Managing Director. In this role, you will lead the day-to-day operations and wellbeing of the local engineering team, while playing a critical part in scaling and strengthening KKR’s long-term engineering capabilities in India. In this role, you will design, build, and maintain scalable data pipelines and platforms that support analytics, reporting, and advanced data science use cases. You will work closely with data analysts, data scientists, and engineering teams to ensure data is reliable, accessible, and production-ready. This role requires a visible, hands-on leader in Gurugram who can support the team locally and build strong partnerships across the organization.
You will also define the technical blueprint for how KKR structures, stores, and uses data to power its AI and platform capabilities, ensuring data integrity, performance, and accessibility for critical firmwide services.

ROLES AND RESPONSIBILITIES 

• Define the target-state architecture for investments data, including scalable data models, ingestion frameworks, data pipelines, real-time processing, and analytics-ready platforms that support front-office, finance, risk, operations, and executive reporting needs.
• Partner with senior leaders across Investments, Technology, Finance, Operations, Risk, Enterprise, Insurance, and Data Governance to align data engineering initiatives with business strategy, platform modernization goals, and regulatory or control requirements.
• Lead the modernization of legacy data environments and reporting processes by introducing scalable, cloud aligned, and well-governed engineering patterns that improve the quality, transparency, timeliness, and reusability of investment data.
• Drive the development of enterprise-grade investment data products and semantic models that enable consistent reporting, analytics, and decision-making across asset classes and investment strategies.
• Build, lead, and develop a high-performing team of data engineers and technical leads, fostering strong execution, talent development, engineering discipline, and a culture of accountability and innovation.
• Establish and enforce best practices for data architecture, software engineering, testing, observability, release management, and platform governance across the Investments Data Engineering organization.
• Manage a portfolio of strategic initiatives, balancing long-term platform transformation with near-term business priorities, while ensuring effective prioritization, stakeholder communication, and measurable outcomes.
• Build and manage data ingestion frameworks across multiple structured and unstructured data sources.

QUALIFICATIONS 

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field; advanced degree preferred.
• 16+ years of experience in data engineering, data architecture, or related technology roles, including significant experience leading teams and delivering large-scale enterprise data platforms.
• Deep domain expertise in investment management, asset management, insurance investments, private markets, or other complex financial services environments, with a strong understanding of investment data and reporting requirements.
• Proven track record of leading enterprise data modernization programs, including data warehouse transformation, pipeline re-architecture, cloud migration, and operating model improvement. Experience with platforms such as Snowflake, BigQuery, Redshift, or Databricks is preferred.
• Strong experience designing and scaling investment data models, ETL/ELT pipelines, and analytics platforms that support complex business processes, multi-asset reporting, and cross-functional use cases.
• Expertise in modern data engineering and platform technologies, including SQL, Python, cloud-based data ecosystems, orchestration tools, and warehouse or lakehouse architectures.
• Knowledge of streaming technologies such as Kafka and Kinesis. Experience with cloud platforms such as AWS, Azure, or GCP.
• Strong understanding of data governance, controls, lineage, security, and auditability requirements within regulated or highly controlled environments.
• Experience leading managers, senior engineers, and cross-functional teams, with a demonstrated ability to influence senior stakeholders and drive alignment across business and technology organizations.
• Excellent communication skills and executive presence, with the ability to translate complex technical concepts into business value and strategic outcomes.
• Demonstrated ability to lead large, high-visibility transformation efforts, operate effectively in ambiguity, and deliver results across multiple concurrent priorities