Job Summary
Manager Data and ML Engineering role focusing on designing building and optimizing scalable data platforms and machine learning solutions using Java advanced JavaScript and advanced Java in a hybrid work model enabling secure high quality data products that power analytics and intelligent applications for global business stakeholders in a collaborative and inclusive environment
Responsibilities
Architect robust data pipelines and platforms that ingest transform and serve large scale datasets using Java and advanced Java to support analytics and machine learning initiatives for diverse business functionsDesign modular and reusable services and APIs using Java and advanced JavaScript that reliably expose data and ML capabilities to internal applications and external partner systemsDevelop production ready machine learning workflows that manage data preparation feature engineering model training and model deployment while ensuring traceability and reproducibility across environmentsImplement strong data quality controls including validation checks anomaly detection data reconciliation and monitoring to maintain trusted datasets for decision makingOptimize performance of batch and real time data processing jobs by tuning code parallelization strategies and resource usage to achieve reliable throughput and cost efficiencyCollaborate closely with data scientists analysts and product teams to translate analytical requirements into scalable engineering solutions that deliver measurable business outcomesEstablish coding standards review practices and version control workflows that improve reliability maintainability and security of data and ML engineering codebasesCoordinate with cloud infrastructure and security teams to ensure data pipelines storage layers and ML services adhere to enterprise standards and regulatory expectationsCreate detailed technical documentation for data models transformation logic interface contracts and operational procedures that help teams onboard and maintain solutions efficientlyEnable robust observability by implementing logging metrics and alerting for data and ML pipelines so that issues are detected early and resolved with minimal business disruptionMentor junior engineers by reviewing work sharing best practices and guiding them through complex engineering problems to raise overall team capability and delivery qualityDrive continuous improvement by evaluating new tools frameworks and design patterns in the Java and JavaScript ecosystem and proposing adoption where they add clear valueAlign engineering activities with organizational sustainability and social impact goals by prioritizing efficient architectures that reduce resource consumption and support ethical use of data
Qualifications
Demonstrate ten to fourteen years of hands on experience in designing and implementing data intensive applications using Java and advanced Java with strong focus on scalability and reliabilityExhibit advanced proficiency with modern JavaScript frameworks and tooling to build or integrate front end or service layer components that interact with data and ML platformsApply solid understanding of machine learning lifecycle including feature pipelines model training evaluation and deployment using industry standard tools and librariesShow proven experience working in hybrid work models by effectively collaborating across onsite and remote teams using structured communication and documentation practicesDisplay strong knowledge of relational and nonrelational databases data warehousing concepts and streaming platforms to support both batch and real time data solutionsUtilize deep expertise in software engineering fundamentals including algorithms data structures design patterns testing strategies and secure coding practicesCommunicate complex technical concepts clearly to technical and nontechnical stakeholders while gathering feedback and aligning solutions to business objectives
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.
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