big data architect

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

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

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