Data Optimization Engineer

at  MP Solutions Ltd

• Design and development of Cloud/Hadoop solutions.
• Undertaking end-to-end project delivery (from inception to post-implementation support), including review and finalization of business requirements, creation of functional specifications and/or system designs, and ensuring that end-solution meets business needs and expectations.
• Analysis of existing designs and interfaces and applying design modifications or enhancements.
• Providing insights and resolution for ad-hoc issues raised by Sandbox users.
• Testing software components and complete solutions (including debugging and troubleshooting) and preparing migration documentation.
• Providing reporting-line transparency through periodic updates on project or task status.

REQUIREMENTS:

• Bachelor’s Degree in Engineering, preferably Computer Science/Engineering.
• Minimum of 5-7 Years of working experience.
• Experienced with the technical analysis and design, development and implementation of Data Lake and cloud solutions.
• Hands on experience in Hadoop and cloud technologies; strong RDBMS concepts and SQL skills. Experience in Data Analytics tools preferably with DataIKU.
• Strong UNIX Shell scripting or Python experience to support data warehousing solutions.
• Process oriented, focused on standardization, streamlining, and implementation of best practices delivery approach.
• Excellent problem solving and analytical skills.
• Excellent verbal and written communication skills.
• Experience in optimizing large data loads.
• Proven teamwork in multi-site/multi-geography organizations.
• Ability to multi-task and function efficiently in a fast-paced environment.
• Self-starter with flexibility and adaptability in a dynamic work environment.
• Should have ability to perform the root cause of Issues and be able to design solution as required.
• Ability to gather user requirements, interface with business partners as required.
• Complete team accountability: deliverables, discipline, consistency.
• Responsible for quantitatively mapping the success of the team.

Please refer the Job description for details