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We are currently looking for a remote Big Data Architect with 7+ years of experience as a Data Architect with design/development background with Java/Scala or Python to join our team.

responsibilities
  • Work closely with business in identifying solution requirements and key case-studies/scenarios to architect data solution for business transformation
    • Participate in Data and Big Data initiatives on a company level
      • Design data analytics solutions by utilizing the data technology stack with Big Data techniques
        • Conduct solution architecture review/audit, calculate and present ROI
          • Create and present solution architecture documents with deep technical details to customer and implementation teams
            • Participate in the full cycle of “pre-sale” activities to prepare technical proposals on customer requests: 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
              • Lead implementation of the solutions from establishing project requirements and goals to solution “go-live”
                • Maintain a strong understanding of technical solutions and architecture design trends and best practices, stay on cutting edge of Data technologies
                  • Constantly grow expertise by gathering and monitoring available EPAM project experience and ongoing projects with clients from different business domains to drive further EPAM business in Data field
                    • Create and follow personal education plan in the technology stack and solution architecture
                      • Share experience, knowledge and vision with EPAM, colleagues and customer teams. Participate in seminars, meet ups, mentoring, training programs. Prepare white papers and presentations
                        requirements
                        • 7+ years experience as a Data Architect with design/development background with Java/Scala or Python
                          • Architecture experience and practice in Data Management, Data Storage, Data Visualization, Disaster Recovery, Integration, Operation and Security
                            • Experience with building traditional Cloud Data Warehouses, Data Lakes
                              • Knowledge of high load and IoT Data Platform architectures and infrastructures
                                • Wide experience in analysis, design, implementation, deployment as well as troubleshooting and rebuilding distributed Linux based platforms and Big Data solutions on premises and in Cloud
                                  • Strong Cloud experience in at least one of the Cloud providers (AWS, Azure, GCP)
                                    • Solid experience in continuous delivery tools and technologies
                                      • Broad experience with Containers and Resource Management systems: Docker, Mesos, Kubernetes/OpenShift, Yarn
                                        • Able to deliver Data Analytics projects and architecture guidelines
                                          • Strong in research, comparison and selection of tools/technologies/approaches to be used
                                            • Practical experience in performance tuning and optimization, bottleneck problem analysis
                                              • Strong communication skills, experienced in team coordination skills and solution implementation supervision
                                                • Good in Agile development methodology, Scrum in particular
                                                  • Solid skills in business analysis, network/stack architecture, troubleshooting, support
                                                    • Fluent English - B2 and higher
                                                      technologies
                                                      • Programming Languages: Java/Scala, Python, SQL, Bash
                                                        • Big Data fundamentals
                                                          • Big Data stack: Hadoop, Yarn, HDFS, MapReduce, Hive, Spark, Kafka, Flume, Sqoop, ZooKeeper
                                                            • NoSQL: Cassandra and HBase & superstructures (Phoenix/Tephra, TitanDB/JanusGraph/Tinkerpop/Gremlin, OpenTSDB, Kylin), CosmosDB, MongoDB
                                                              • Stream processing: Kafka Streams/Spark Streaming
                                                                • Background in traditional data warehouse and business intelligence stacks (ETL, MPP Databases, Tableau, Microsoft Power BI, SAP Business Objects)
                                                                  • Data Visualization: Power BI, Tableau, QlikView
                                                                    • Operation: Cluster operation, Cluster planning
                                                                      • Flow Management: Apache Oozie, Informatica Big Data, Talend, Airflow
                                                                        • Search: Solr, Elasticsearch/ELK
                                                                          • In-Memory: Ignite, Redis
                                                                            • Cloud (at least one provider: AWS/Azure/GCP): Storage, Compute, Networking, Identity and Security, NoSQL, RDBMS and Cubes, Big Data Processing, Queues and Stream Processing, Serverless
                                                                              • Architecture concepts: Application Design, Integration Design, Layered Architecture, Synthesis of Solutions, Architecture Bugs evaluations

                                                                                benefits for locations

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                                                                                For you
                                                                                • Paid time off
                                                                                • Paid sick leave days
                                                                                • Medical insurance
                                                                                • Stable income
                                                                                For your comfortable work
                                                                                • 100% remote work forever
                                                                                • Free licensed software
                                                                                • Possibility to work on your own device (BYOD)
                                                                                • Stable workload
                                                                                • Relocation opportunities
                                                                                • Flexible engagement models
                                                                                For your growth
                                                                                • Free trainings for technical and soft skills
                                                                                • Free access to LinkedIn Learning platform
                                                                                • Language courses
                                                                                • Free access to internal and external e-Libraries
                                                                                • Certification opportunities
                                                                                • Skill advisory service
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