Big Data Engineer

Orion InnovationEdison, NJ
15h

About The Position

Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education. Job Responsibilities: Requirement analysis, requirement gathering, design, business impact analysis, gap analysis, estimation, development, testing, coding, code review, unit testing and deployment of the application. Design, build, install, configure, and support Hadoop (Big Data). Design and implement big data pipelines to ingest and process data in real-time and monitor for data miss or error in progress to ensure that data reaches the end system. Measure the performance of various APIs and implement optimization on slow services to enhance the responsiveness of the system. Deliver functional enhancements to the existing big data applications. Provide inputs on solution architecture based on evaluation/understanding of solution alternatives, frameworks, and products. Develop Hadoop batch jobs for data extraction from multiple unstructured and structured data sources for populating into various repositories (Hadoop, Neo4J, MongoDB, Apache SOLR). Interact with clients to elicit architectural and non-functional requirements such as performance, scalability, reliability, availability, maintainability. Participate in designing the data model structured data in RDBMS into a graph database solution and NoSQL database solution. Develop near real-time data processing solutions using Kafka and Spark Streaming. Participate in designing Spark architecture with Databricks and Structured Streaming. Set up Microsoft Azure with Databricks, and Databricks Workspace for business analytics. Contribute to the automate build process by using Jenkins and Ansible to achieve continuous integration and continuous deployment.

Requirements

  • Master’s in Computer Science/Applications, Information Technology/Systems or Electronics/Electrical Engineering + minimum 1 year experience as Big Data Engineer, Data Engineer, Data Engineering Specialist, Data Warehousing Analyst or related occupation.
  • Must be willing to travel/relocate to anywhere in the US.

Responsibilities

  • Requirement analysis, requirement gathering, design, business impact analysis, gap analysis, estimation, development, testing, coding, code review, unit testing and deployment of the application.
  • Design, build, install, configure, and support Hadoop (Big Data).
  • Design and implement big data pipelines to ingest and process data in real-time and monitor for data miss or error in progress to ensure that data reaches the end system.
  • Measure the performance of various APIs and implement optimization on slow services to enhance the responsiveness of the system.
  • Deliver functional enhancements to the existing big data applications.
  • Provide inputs on solution architecture based on evaluation/understanding of solution alternatives, frameworks, and products.
  • Develop Hadoop batch jobs for data extraction from multiple unstructured and structured data sources for populating into various repositories (Hadoop, Neo4J, MongoDB, Apache SOLR).
  • Interact with clients to elicit architectural and non-functional requirements such as performance, scalability, reliability, availability, maintainability.
  • Participate in designing the data model structured data in RDBMS into a graph database solution and NoSQL database solution.
  • Develop near real-time data processing solutions using Kafka and Spark Streaming.
  • Participate in designing Spark architecture with Databricks and Structured Streaming.
  • Set up Microsoft Azure with Databricks, and Databricks Workspace for business analytics.
  • Contribute to the automate build process by using Jenkins and Ansible to achieve continuous integration and continuous deployment.
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