Big Data Engineer

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.