Associate Process Manager
- eClerx
- 0 - 13 years
- Mumbai
- 23 days ago
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Job Description
We are looking for a skilled Big Data Engineer to join our team as an Associate Process Manager. The ideal candidate will have experience in big data engineering and be able to work with large datasets.
Roles and Responsibility
- Design, develop, and implement big data solutions using various technologies.
- Collaborate with cross-functional teams to identify business requirements and develop solutions.
- Develop and maintain large-scale data pipelines and architectures.
- Ensure data quality and integrity by implementing data validation and testing procedures.
- Optimize big data systems for performance and scalability.
- Provide technical guidance and support to junior team members.
Job Requirements
- Strong understanding of big data technologies such as Hadoop, Spark, and NoSQL databases.
- Experience with data processing frameworks such as MapReduce and Hive.
- Knowledge of data modeling and data warehousing concepts.
- Excellent problem-solving skills and attention to detail.
- Ability to work in a fast-paced environment and meet deadlines.
- Strong communication and collaboration skills.
About Company
eClerx Services Ltd. is a leading provider of outsourcing services, including customer support, content development, and data analytics. We are committed to delivering high-quality services to our clients and providing opportunities for professional growth and development to our employees.
Disclaimer - This job description has been sourced from a public domain and may have been modified by Naukri.com to improve clarity for our users. We encourage job seekers to verify all details directly with the employer via their official channels before applyingJob Classification
Industry: MiscellaneousFunctional Area / Department: Customer Success, Service & OperationsRole Category: Service DeliveryRole: Service Delivery - OtherEmployement Type: Full timeContact Details:
Company: eClerxLocation(s): Mumbai
Keyskills: hive data analytics data pipelines data engineer data processing data warehousing data engineering nosql customer support analytics data quality data modeling mapreduce spark data systems hadoop big data nosql databases
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