Job Summary
This hybrid day shift role is for a seasoned technical lead with deep hands on experience in Azure Data Factory and Databricks guiding complex data engineering initiatives for an international organization. The role focuses on architecting robust data pipelines and analytics solutions mentoring technical teams and collaborating with business stakeholders. Experience in life and annuities insurance is preferred to enhance domain driven design and insight generation across enterprise data plat
Responsibilities
Drive end to end design and implementation of scalable data pipelines using Azure Data Factory and Databricks to support enterprise analytics and reporting needs across the organizationLead technical solutioning for complex data integration scenarios by defining patterns for ingestion transformation and orchestration that ensure reliability performance and maintainabilityCoordinate hybrid model delivery activities by planning onsite and remote work schedules that optimize collaboration with cross functional partners and maintain consistent progress on critical milestonesProvide technical guidance to data engineers and developers by reviewing code design artifacts and deployment approaches to uphold high standards of quality security and operational stabilityCollaborate with business and product stakeholders by translating analytical and reporting requirements into well structured Azure based data solutions that deliver measurable value to customers and internal teamsOptimize Databricks workloads by tuning clusters jobs and queries to improve cost efficiency execution speed and resource utilization while enforcing best practices for workspace organization and governanceImplement robust monitoring logging and alerting for Azure Data Factory and Databricks jobs by leveraging native tools and dashboards to proactively identify issues and reduce downtimeEnsure data quality and consistency across data pipelines by designing validation rules reconciliation checks and error handling strategies that strengthen trust in curated datasets and downstream analyticsCoordinate secure data access and compliance alignment by working with security and risk partners to apply appropriate controls masking and role based permissions across data platformsSupport project planning and estimation activities by providing realistic effort assessments for data engineering tasks enabling accurate timelines and resource allocation for delivery teamsPartner with architecture and infrastructure groups by aligning solutions with enterprise standards reference architectures and cloud governance guidelines to maintain long term sustainabilityContribute to continuous improvement initiatives by capturing lessons learned researching emerging Azure data services and proposing enhancements that increase productivity and innovation across projectsEngage with domain experts in life and annuities insurance when available by shaping data models metrics and analytics that reflect key business processes and improve decision making for policy and claims outcomes
Qualifications
Demonstrate extensive hands on expertise with Azure Data Factory including pipeline development data flow configurations and integration runtime management for complex enterprise workloadsApply strong Databricks knowledge by building performant notebooks jobs and workflows that leverage Spark based processing for batch and near real time data transformation scenariosBring proven experience in designing cloud data architectures that include storage choices compute strategies and integration patterns aligned with organizational standards and performance expectationsUtilize solid data engineering fundamentals such as modeling ETL design optimization and testing to create resilient data solutions that are easy to maintain and extend over timeLeverage any background in life and annuities insurance to interpret business concepts such as policy lifecycle underwriting claims and actuarial analysis when designing data structures and analytics outputsCommunicate effectively with technical and nontechnical partners by explaining solution approaches dependencies and risks in clear language that supports informed decisions and collaborative planningOperate comfortably in a hybrid work environment by using collaboration tools disciplined documentation and regular touchpoints to maintain transparency and alignment across onsite and remote participants
Certifications Required
Azure Data Engineer Associate or equivalent cloud data certification preferred
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.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.
