Insurance Data Engineering - Data Engineer

KKR
Gurugram
Workplace: OnsiteFull timeFunction: Insurance & ActuarialExperience: 5-8 yearsSkills: ["Communication","Cross-functional collaboration","Ownership mindset","Problem-solving","Debugging"]

Build and operate production-grade data platforms on AWS for KKR’s insurance business. Own end-to-end data pipelines—ingestion, orchestration, transformation, storage, and governance—using a modern lakehouse stack (Apache Iceberg, AWS Glue, Snowflake). Develop scalable ETL/ELT and Spark processing jobs, ensure data quality and lineage across systems, and optimize for reliability, performance, and cost. Collaborate with data scientists and analysts to deliver governed data products for analytics and business decisions.

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FursaFursa
KKR
KKR
2 days ago

Insurance Data Engineering - Data Engineer

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Last checked: 3 hours agoStatus: Live

Job Summary

Build and operate production-grade data platforms on AWS for KKR’s insurance business. Own end-to-end data pipelines—ingestion, orchestration, transformation, storage, and governance—using a modern lakehouse stack (Apache Iceberg, AWS Glue, Snowflake). Develop scalable ETL/ELT and Spark processing jobs, ensure data quality and lineage across systems, and optimize for reliability, performance, and cost. Collaborate with data scientists and analysts to deliver governed data products for analytics and business decisions.
Location: Gurugram
Workplace: Onsite
Employment Type: Full time
Job Function: Insurance & Actuarial
Seniority: Mid level

Key Responsibilities

  • •Design, build, and maintain scalable fault-tolerant data pipelines and ETL/ELT for multiple data types.
  • •Own end-to-end pipeline orchestration, including scheduling, dependency management, retries, SLAs, and observability.
  • •Build and manage lakehouse data assets on Apache Iceberg, including partitioning, schema evolution, time-travel, and maintenance.
  • •Develop and operate large-scale data processing jobs using Apache Spark and AWS Glue Spark jobs.
  • •Ensure data quality, integrity, lineage, and security; integrate data from APIs, databases, streaming feeds, and third-party tools.

Key Requirements

  • •5-8 years of hands-on data engineering experience building production data pipelines.
  • •Strong proficiency in Python for data engineering and automation.
  • •Advanced SQL and strong experience with relational databases such as PostgreSQL or MySQL.
  • •Mandatory experience operating a workflow orchestration tool in production (e.g., Apache Airflow or Dagster).
  • •Hands-on experience with lakehouse and AWS data services (Apache Iceberg, AWS Glue, and Snowflake).
Experience:5-8 yearsFinancial servicesInsuranceLakehouse
Skills:CommunicationCross-functional collaborationOwnership mindsetProblem-solvingDebugging
Languages:English
Tech Stack:AWSS3GlueEMRLambdaAthenaKinesisRedshiftIAMApache SparkApache IcebergSnowflakeAWS Glue Data CatalogSnowflake HorizonApache AirflowDagsterDockerKubernetesAmazon EKSTerraform

Company Brief

KKR
Global investment firm providing alternative asset management and capital markets services across private equity, credit, real assets, and hedge funds, serving institutional and private clients worldwide.
Industry: Asset Management
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: New York, United States
Founded: 1976
WebsiteLinkedIn