Job Summary
This hybrid role for a technical lead focuses on designing and implementing scalable data architecture solutions that enable advanced analytics and business intelligence. The role spans data visualization cloud data warehouse engineering data modeling DevOps practices and Python based development. The technical lead will drive robust data platforms that empower stakeholders to make informed decisions and create measurable value for clients and society.
Responsibilities
Design and guide end to end data architecture solutions that connect source systems to cloud data warehouse platforms and analytics tools to deliver reliable insights for business decision making.Lead the creation of enterprise grade data models that support reporting self service analytics and advanced data products while ensuring consistency performance and scalability.Develop and optimize Python based data pipelines that ingest transform and validate data from diverse sources to maintain high standards of data quality and timeliness.Apply DevOps practices across analytics and data engineering workflows by automating build test and deployment processes for data services and visual analytics assets.Implement and maintain cloud data warehouse structures including schemas tables views and access patterns to support efficient querying and downstream data visualization.Create and refine interactive data visualization solutions using modern tools that translate complex datasets into clear narratives for business and operations teams.Collaborate with product owners and domain experts to translate requirements into technical designs that balance performance cost and future extensibility of data platforms.Establish and enforce coding standards data modeling conventions and data governance practices that improve reliability and reusability of analytics assets across projects.Optimize query performance and storage strategies in cloud data warehouse environments to reduce processing time and resource usage while preserving analytical flexibility.Mentor team members on data engineering Python programming and visualization best practices to raise overall delivery quality and encourage continuous improvement.Coordinate with cloud and infrastructure teams to ensure secure resilient and compliant deployment of data pipelines and visualization solutions in the hybrid work model.Monitor and troubleshoot production data workflows and reporting assets during day shift to maintain availability and accuracy for critical business processes without requiring travel.Document architectures data flows and operational procedures in a clear and structured manner so that stakeholders can understand maintain and evolve the solutions over time.
Qualifications
Demonstrate strong proficiency in building interactive data visualization solutions using contemporary business intelligence tools and storytelling techniques for analytical audiences.Bring extensive hands on experience with DevOps principles in data environments including version control automation testing and continuous delivery for analytics components.Exhibit advanced Python programming skills for data processing automation and integration with cloud services and visualization platforms in production scenarios.Show deep expertise with cloud data warehouse technologies and patterns such as star schemas and columnar storage tuned for analytical workloads and large scale reporting.Display solid knowledge of data modeling concepts including dimensional modeling normalization practices and metadata management applied to complex enterprise datasets.Provide proven experience as a data architect designing end to end data solutions that align with organizational strategy security expectations and regulatory requirements.Possess eight to ten years of overall experience in data engineering and analytics environments with consistent responsibility for solution design and technical decision making.Adapt effectively to hybrid work arrangements by using collaboration tools and structured communication to coordinate delivery activities across distributed teams.Maintain strong problem solving and analytical skills with the ability to diagnose data issues and propose pragmatic solutions that protect business continuity.Ally with business partners to understand data consumption patterns and refine modeling and visualization so that information becomes more actionable and socially impactful.
Certifications Required
Preferred certifications include cloud data engineering or architecture credentials and Python or data visualization platform certifications.
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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