Job Summary
Sr Developer role in a global organization focusing on data engineering solutions for life and annuities insurance using Databricks SQL Databricks Workflows and PySpark. The role involves building scalable data pipelines optimizing analytical workloads and ensuring high quality data products in a hybrid work model with day shift and no travel.
Responsibilities
Design robust data pipelines in Databricks using Databricks SQL and PySpark to transform complex life and annuities insurance data into reliable analytics ready datasetsDevelop reusable PySpark modules that standardize ingestion cleansing and enrichment of policy claims and actuarial data while meeting performance expectations and coding standardsConfigure and manage Databricks Workflows to orchestrate end to end batch and near real time data processing jobs supporting reporting and analytics needs for insurance stakeholdersOptimize Databricks SQL queries and PySpark jobs by tuning partitions caching strategies and cluster configurations to achieve efficient resource usage and faster insightsImplement data quality checks validation rules and reconciliation processes that improve the accuracy and completeness of life and annuities insurance datasets used across business functionsCollaborate with business analysts and actuaries to translate insurance product rules policy events and financial calculations into clear and maintainable data engineering logicDocument technical designs job dependencies transformation logic and operational procedures to ensure transparency maintainability and smooth knowledge transfer within the teamPartner with testing and operations teams to define test cases support defect resolution and enable stable deployment of Databricks solutions into production environmentsMonitor production workflows in Databricks investigate failures or performance regressions and implement corrective actions that protect data reliability and service commitmentsApply secure coding practices implement access controls and follow compliance guidelines relevant to financial and insurance data handling across all data engineering activitiesContribute to continuous improvement by identifying automation opportunities refactoring legacy code and adopting emerging Databricks features that deliver better outcomes for the companySupport business reporting and advanced analytics initiatives by exposing curated data models reusable views and standardized metrics for life and annuities insurance use casesWork effectively in a hybrid environment by coordinating with on site and remote team members ensuring timely communication and consistent progress on shared deliverables
Qualifications
Possess professional experience between six and eight years in data engineering or related roles with a strong focus on large scale analytics solutionsDemonstrate deep proficiency in Databricks SQL including development of complex queries views and performance optimized data models for analytical consumptionShow hands on expertise in PySpark programming including data frame operations user defined functions and performance tuning techniques on distributed datasetsExhibit practical experience configuring and managing Databricks Workflows including job scheduling dependency handling and monitoring of production pipelinesBring solid domain knowledge in life and annuities insurance including familiarity with policies riders premiums benefits and related data structuresDisplay strong understanding of data warehousing concepts dimensional modeling and best practices for building curated layers supporting reporting and analyticsApply sound knowledge of software engineering practices such as version control code review and modular design to maintain high quality data engineering solutionsCommunicate effectively with cross functional partners by explaining technical designs in business friendly language and incorporating feedback into implementation plansAdhere to organizational standards for security compliance and documentation while contributing ideas that enhance efficiency and long term maintainability of solutions
Certifications Required
Preferred certifications include Databricks Data Engineer Associate or Professional and cloud platform certifications relevant to data engineering
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
