Data Analytics Engineer
Summary
Builds and maintains RESTful APIs and data pipelines using Python/Scala, SQL, and big-data tools like Spark and Kafka to process and deliver analytics data.
Responsibilities
Analyze, design, develop, and implement RESTful services and APIs. Be involved in the development life cycle and perform definition and feasibility analysis. Implement, integrate, and document a variety of software platforms through the REST API framework. Apply the latest software design techniques and contribute to the technical design of new solutions. Modify existing programs, prepare test data and functional specifications. Troubleshoot issues and solve problems, identify potential process improvement areas. Implement common APIs based on architecture guidelines and frameworks Write object-oriented, clean, and maintainable code. Delivery quality results on time with minimal supervision.
Requirement
1-3 years of relevant experience in data engineering/analytics space. Expertise in SQL and data analysis and strong hands-on expertise with atleast one programming language: Python and/or Scala. Strong knowledge in one or more of the following big data frameworks: Hive, Spark, Kafka etc. Strong expertise in big data, data warehousing, and hands-on experience of using DevX tools and CI/CD frameworks. Experience developing solutions for cloud computing services using cloud based infrastructure and services. Experience developing and maintaining data warehouses in big data solutions. Up to date on industry trends within the analytics space from a data acquisition processing, engineering, and management perspective. Experience in agile development. Strong people skills, specifically in collaboration and teamwork.
Analyze, design, develop, and implement RESTful services and APIs. Be involved in the development life cycle and perform definition and feasibility analysis. Implement, integrate, and document a variety of software platforms through the REST API framework. Apply the latest software design techniques and contribute to the technical design of new solutions. Modify existing programs, prepare test data and functional specifications. Troubleshoot issues and solve problems, identify potential process improvement areas. Implement common APIs based on architecture guidelines and frameworks Write object-oriented, clean, and maintainable code. Delivery quality results on time with minimal supervision.
Requirement
1-3 years of relevant experience in data engineering/analytics space. Expertise in SQL and data analysis and strong hands-on expertise with atleast one programming language: Python and/or Scala. Strong knowledge in one or more of the following big data frameworks: Hive, Spark, Kafka etc. Strong expertise in big data, data warehousing, and hands-on experience of using DevX tools and CI/CD frameworks. Experience developing solutions for cloud computing services using cloud based infrastructure and services. Experience developing and maintaining data warehouses in big data solutions. Up to date on industry trends within the analytics space from a data acquisition processing, engineering, and management perspective. Experience in agile development. Strong people skills, specifically in collaboration and teamwork.