KKR's Gurugram office provides best in class services and solutions to our internal stakeholders and clients, drive organization wide process efficiency and transformation, and reflects KKR's global culture and values of teamwork and innovation. The office will contain multifunctional business capabilities and will be integral in furthering the growth and transformation of KKR.

TECHNOLOGY ORGANIZATION OVERVIEW
KKR’s Technology team is responsible for building and supporting the firm’s technological foundation including a globally distributed infrastructure, information security, and application and data platforms. The team drives a culture of technology excellence across the firm through efficient workflow automation, democratization of data through modern data and collaboration platforms, and more recently through research and development of Generative AI based tools and services. Technology is regarded as a key business enabler at KKR and is an important accelerator to drive towards global scale creation and business process transformation. The Technology team consists of highly technical and business-centric technologists with the ability to form strong partnerships across all of our businesses. A dedicated Program Management function along with the Product Managers drive execution discipline across multiple technology teams with a goal to consistently deliver excellence serving our business needs.

POSITION SUMMARY
We are looking for a Data Engineer who is passionate about building scalable, reliable, and well-governed data pipelines and curated data environments. You will work closely with product managers, solution architects, business resources, and other full-stack engineers to deliver end-to-end data solutions that are secure, scalable, and with high performance. This role will support Insurance platforms in a regulated financial services environment, including Retirement, Life, Reinsurance, and Institutional businesses.

KEY RESPOSNSIBLITIES:
• Design, build, test, and maintain scalable data pipelines (batch and/or near real-time) for core Insurance systems (e.g., policy administration, billing, claims, commissions, reinsurance, and finance).
• Ingest data from source systems (APIs, files, event streams) into the enterprise data platform (e.g., Snowflake), ensuring reliability, performance, and strong controls.
• Develop and maintain canonical data models and curated datasets to power analytics, reporting, and downstream integrations.
• Implement data quality checks, reconciliations, and automated testing to ensure accuracy and completeness of financial and operational data.
• Partner with cross-functional stakeholders (actuarial, finance, operations, technology) to translate business requirements into well-defined data mappings, transformations, and data products.
• Establish and maintain documentation, metadata, and lineage; contribute to data governance practices including definitions, ownership, and change management.
• Monitor pipeline jobs, troubleshoot failures, resolve errors, and perform root-cause analysis; implement preventative fixes and improve runbooks/operational playbooks.
• Optimize warehouse performance and cost through efficient SQL patterns, clustering/partitioning strategies, and thoughtful pipeline design.
• Contribute to engineering best practices including code reviews, version control, CI/CD for data pipelines, and reusable frameworks/components.

Qualifications Required
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
• 4+ years of experience building and supporting production data pipelines and data products
• Strong proficiency in SQL, including complex querying and performance optimization
• Hands-on experience with cloud data warehouses (Snowflake preferred) and modern ELT/ETL patterns
• Strong understanding of data modeling (dimensional modeling, SCDs, and/or Data Vault concepts)
• Experience with version control systems (Git) and collaborative engineering workflows.
• Strong problem-solving skills, attention to detail, and ability to work independently as well as in a collaborative team environment

Preferred skillset
• Experience with orchestration and workflow tools (e.g., Airflow) and/or transformation frameworks (e.g., dbt)
• Experience with cloud platforms (AWS, Azure, or GCP) and data lake patterns (e.g., S3/ADLS + parquet)
• Exposure to CI/CD and DevOps practices for data (testing, automated deployments, environment promotion)
• Understanding of security, privacy, and access control best practices for sensitive data (PII), including RBAC and masking/encryption
• Experience with data observability/monitoring and alerting practices (pipeline SLAs, anomaly detection, job health)
• Prior experience working in agile or scrum teams
• Experience in Insurance, Financial Services, or other highly regulated environments
• Familiarity with Insurance domains and systems such as policy administration, billing, claims, reinsurance, and insurance accounting concepts