27 days ago
Chennai, IndiaSenior / Staff+
Responsibilities
- Design scalable AWS data architectures supporting underwriting, pricing, claims, and policy administration workflows.
- Build and optimize PySpark and Python data pipelines in Databricks for structured and semi-structured insurance data.
- Develop reusable data models and canonical datasets for policies, coverages, claims, and reinsurance treaties.
- Implement data quality rules, validation checks, reconciliation processes, monitoring, alerting, backup, recovery, and environment management.
- Collaborate with insurance business stakeholders and enterprise architects to translate requirements into governed data engineering solutions.
- Document data flows, data dictionaries, architecture blueprints, and source-to-consumption traceability.
- Profile datasets, tune performance, modernize legacy platforms, and decommission redundant assets.
- Mentor peers and junior engineers on PySpark, data modeling, and cloud engineering practices.
Requirements
- 8–12 years of experience in data engineering or data architecture roles delivering production-grade enterprise solutions.
- Strong hands-on expertise with AWS data, compute, storage, processing, orchestration, and security services.
- Advanced proficiency in PySpark and Python for scalable transformations, unit tests, and reusable utility frameworks.
- Proven experience developing, optimizing, and operating Databricks notebooks, jobs, and clusters.
- Deep understanding of property and casualty insurance concepts, including policies, coverages, rating factors, claims lifecycle, and regulatory reporting.
- Knowledge of dimensional and relational data modeling for data marts and semantic layers.
- Strong SQL, data profiling, and data quality assessment skills.
- Ability to communicate complex data topics clearly and collaborate with distributed hybrid teams.
- Familiarity with DevOps and DataOps practices, including version control, continuous integration, automated testing, and environment promotion.
- Commitment to continued learning in AWS, Databricks, and open-source data engineering technologies.
Tech Stack
Categories
Data Engineering
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.