Development of proposals for implementation and design of scalable big data architecture
Participation in customer's workshops and presentation of the proposed solution
Design, implement, and deploy high-performance, custom applications at scale on Hadoop
Define and develop network infrastructure solutions to enable partners and clients to scale NoSQL and relational database architecture for growing demands and traffic
Define common business and development processes, platform and tools usage for data acquisition, storage, transformation, and analysis
Develop roadmaps and implementation strategy around data science initiatives including recommendation engines, predictive modeling, and machine learning
Review and audit of existing solution, design and system architecture
Perform profiling, troubleshooting of existing solutions
Create technical documentation
Requirements
Strong knowledge of programming and scripting languages such as Java, Python, or Scala
Participation in designing, development, or maintenance of a distributed application
Experience with major Big Data technologies and frameworks including but not limited to Hadoop, MapReduce, Apache Spark, Hive, Kafka, Apache Flink, Flume, ZooKeeper, HBase, MongoDB, and Cassandra
Experience with Big Data solutions developed in large cloud computing infrastructures such as Amazon Web Services, Azure Cloud, or Google Cloud
Experience in client-driven large-scale implementation projects
Data Science and Analytics experience is a plus (Machine Learning, Recommendation Engines, Search Personalization, Deep Learning)
Technical team leading and team management experience, deep understanding of Agile (Scrum), RUP programming process
Strong experience in applications design, development, and maintenance
Solid knowledge of design patterns, refactoring concepts, unit tests, and CI/CD
Practical expertise in performance tuning and optimization, bottleneck problems analysis
