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
Über Cognizant
Cognizant (NASDAQ: CTSH) i ist ein Technologiedienstleister und Entwickler von KI-Lösungen. Wir schlagen die Brücke zwischen KI-Investitionen und echtem unternehmerischem Mehrwert, indem wir ganzheitliche Full-Stack-KI-Lösungen für unsere Kunden entwickeln. Mit unserer fundierten Branchen-, Prozess- und Engineering-Expertise integrieren wir die spezifischen Anforderungen von Unternehmen passgenau in Technologiesysteme. So entfalten wir das menschliche Potenzial, erzielen greifbare Ergebnisse und sichern globalen Unternehmen in einer sich rasant wandelnden Welt den entscheidenden Vorsprung. Erfahren Sie mehr unter cognizant.ai oder @cognizant.
Zusätzliche Informationen zur Beschäftigung
Die Vergütungsinformationen sind zum Zeitpunkt der Veröffentlichung dieser Stellenausschreibung korrekt. Cognizant behält sich das Recht vor, diese Informationen jederzeit unter Beachtung der geltenden gesetzlichen Bestimmungen zu ändern.
Bewerberinnen und Bewerber können verpflichtet sein, an Vorstellungsgesprächen persönlich oder per Videokonferenz teilzunehmen. Darüber hinaus kann es erforderlich sein, bei jedem Gespräch einen gültigen staatlichen Lichtbildausweis vorzulegen.
Cognizant ist ein Arbeitgeber mit Chancengleichheit. Ihre Bewerbung und Kandidatur werden nicht aufgrund von Rasse, Hautfarbe, Geschlecht, Religion, Glaubensbekenntnis, sexueller Orientierung, Geschlechtsidentität, nationaler Herkunft, Behinderung, genetischen Informationen, Schwangerschaft, Veteranenstatus oder sonstiger durch bundes‑, landes‑ oder kommunalrechtliche Vorschriften geschützter Merkmale berücksichtigt oder abgelehnt.