Ranked as #12 on Forbes’ List of 25 Fastest Growing Public Tech Companies for 2017, EPAM is committed to providing our global team of 25,900+ EPAMers with inspiring careers from day one. EPAMers lead with passion and honesty, and think creatively. Our people are the source of our success and we value collaboration, try to always understand our customers’ business, and strive for the highest standards of excellence. No matter where you are located, you’ll join a dedicated, diverse community that will help you discover your fullest potential.
Currently we are looking for permanent, technically hands-on Big Data Architect to join our London team and lead on various strategic client projects.
These are high profile and visible roles within both EPAM and onsite with our clients where you will have a high degree of flexibility to own and enhance the technical landscapes.
Design data analytics solutions by utilizing the Big Data technology stack;
Create and present solution architecture documents with deep technical details;
Work closely with business in identifying solution requirements and key case-studies/scenarios for future solutions;
Conduct solution architecture review/audit, calculate and present ROI;
Lead implementation of the solutions from establishing project requirements and goals to solution "go-live";
Participate in the full cycle of pre-sale activities: direct communications with customers, RFP processing, the development of proposals for implementation and design of the solution, presentation for proposed solution architecture to the customer and participate in technical meetings with customer representatives;
Create and follow personal education plan in the technology stack and solution architecture;
Maintain a strong understanding of industry trends and best practices;
Get involved in engaging new clients to further drive EPAM business in the Big Data space.
Strong ‘hands-on’ experience as a Big Data Architect with a solid design/development background with Java, Scala, or Python;
Experience delivering data analytics projects and architecture guidelines;
Experience in big data solutions on premises and on the cloud (Amazon Web Services, Microsoft Azure, Google Cloud);
Production project experience in at least one of the Big Data technologies;
Batch processing: Hadoop and MapReduce / Spark / Hive;
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