Skill: Kafka, Spark, Bigdata
Experience: 7 to 13 years
Location: Bangalore
Job Description
- Design and implement complex data solutions using Big Data, Spark, and Kafka Streaming technologies.
- Lead and guide a team of data engineers in delivering high-quality and innovative solutions.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
- Develop and maintain data pipelines and workflows to ensure efficient and accurate data processing.
- Identify and troubleshoot data quality and performance issues.
- Stay up-to-date with industry trends and best practices in data engineering to drive innovation.
- Manage and prioritize multiple projects and tasks to meet tight deadlines.
- Communicate effectively with stakeholders at all levels to provide updates and recommendations.
- Implement and maintain data security and governance measures to ensure compliance with regulations.
- Mentor and train junior data engineers to enhance their skills and knowledge.
- Continuously evaluate and improve existing data processes and systems to optimize efficiency.
- Assist in the evaluation and implementation of new data technologies and tools.
- Participate in regular team meetings and provide input in decision-making processes.
- Take ownership of data engineering projects and drive them to successful completion.
- Be a proactive problem-solver and provide innovative solutions to complex data challenges.
Job Qualifications
- Extensive Knowledge Of Big Data Technologies: A Lead Data Engineer At Visa Should Have A Strong Understanding Of Big Data Technologies Such As Hadoop, Spark, And Kafka. They Should Be Proficient In Designing And Developing Data Pipelines And Data Warehousing Solutions Using These Technologies.
- Experience With Real-Time Data Processing: As A Lead Data Engineer, The Candidate Should Have Experience With Real-Time Data Processing Using Technologies Like Kafka Streaming. They Should Be Able To Design And Implement Scalable And Fault-Tolerant Streaming Data Pipelines.
- Expertise In Data Modeling And Database Design: A Strong Foundation In Data Modeling And Database Design Is Essential For A Lead Data Engineer At Visa. They Should Be Able To Design Efficient And Optimized Data Models For Large-Scale Data Processing And Analytics.
- Team Management Skills: Being A Lead Data Engineer, The Candidate Should Have Excellent Team Management Skills. They Should Be Able To Lead And Mentor A Team Of Data Engineers, Providing Technical Guidance And Ensuring The Successful Delivery Of Projects.
- Business Acumen: A Successful Lead Data Engineer At Visa Should Possess Strong Business Acumen And Be Able To Understand The Business Needs And Requirements. They Should Be Able To Translate Those Requirements Into Technical Solutions And Make Data-Driven Decisions.
Sobre nosotros:
Cognizant (NASDAQ: CTSH) es un arquitecto de soluciones de IA y proveedor de servicios tecnológicos que traduce la inversión en inteligencia artificial en valor empresarial real mediante soluciones de IA de stack completo adaptadas a cada cliente. Su profundo conocimiento de la industria, los procesos y la ingeniería le permite integrar el contexto único de cada organización en sistemas tecnológicos que amplifican el potencial humano, generan un impacto real en el negocio y mantienen a las grandes empresas globales un paso adelante en un mundo en constante cambio. Para más información, visita www.cognizant.es o síguenos en @cognizant.
Información adicional de empleo
La información de compensación es precisa a la fecha de esta publicación. Cognizant se reserva el derecho de modificar esta información en cualquier momento, sujeto a la legislación aplicable.
Es posible que se requiera que los solicitantes asistan a entrevistas en persona o por videoconferencia. Además, es posible que se requiera que los candidatos presenten su identificación actual emitida por el estado o gobierno durante cada entrevista.
Cognizant es un empleador que ofrece igualdad de oportunidades. Tu solicitud y candidatura no serán consideradas en base a raza, color, sexo, religión, credo, orientación sexual, identidad de género, origen nacional, discapacidad, información genética, embarazo, condición de veterano o cualquier otra característica protegida por las leyes federales, estatales o locales.
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