Data System engineer

Data System EngineerLocation: Alpharetta, Georgia 30022 Hybrid 3 days a week onsite Potential to convertTop skills: Python, spark, shell scripting, experience with databases Snowflake Most team members are in Alpharetta, GA The team is ETL, data warehousing Looking for Data system engineer Cloud side SDLC can take place as design Batch streaming on cloud premises The databases use is Sybase IQ, DB2 Snowflake (Snowflake is highly preferred in database) Client platform is AWS they are moving to Azure Potential to convert not considering Visa candidates Data engineering experience moving large amounts of data in python Looking for DevOps exp. Jenkins experience. Financial exp. Is not needed is a good plus. Looking for mid-level candidates. 4-years’ experience would also be fine. System design experience. NoSQL is a plus not a must have. Nice to have: Collibra, Terraform, Java, Golang, Ruby, Machine Learning Operation deployment must not have.The Data System Engineer will be responsible for tasks such as data engineering, data modeling, ETL processes, data warehousing, and data analytics & science. Our platform run both on premise and on the cloud (AWS/Azure). Knowledge/Skills: Able to establish, modify or maintain data structures and associated components according to design Understands and documents business data requirements Able to come up with Conceptual and Logical Data Models at Enterprise, Business Unit/Domain Level Understands XML/JSON and schema development/reuse, database concepts, database designs, Open Source and NoSQL concepts Partners with Sr. Data Engineers and Sr. Data architects to create platform level data models and database designs Takes part in reviews of own work and reviews of colleagues' work Has working knowledge of the core tools used in the planning, analyzing, designing, building, testing, configuring and maintaining of assigned application(s) Able to participate in assigned teams software delivery methodology (Agile, Scrum, Test-Driven Development, Waterfall, etc.) in support of data engineering pipeline development Understands infrastructure technologies and components like servers, databases, and networking concepts Write code to develop, maintain and optimized batch and event driven for storing, managing, and analyzing large volumes of structured and unstructured data both Metadata integration in data pipelines Automate build and deployment processes using Jenkins across all environments to enable faster, high-quality releasesQualification: Up to 4 years of software development experience in a professional environment and/or comparable experience such as: Understanding of Agile or other rapid application development methods Exposure to design and development across one or more database management systems DB2, SybaseIQ, Snowflake as appropriate Exposure to methods relating to application and database design, development, and automated testing Understanding of big data technology and NOSQL design and development with variety of data stores (document, column family, graph, etc.) General knowledge of distributed (multi-tiered) systems, algorithms, and relational & non-relational databases Experience with Linux and Python scripting as well as large scale data processing technology such as spark Exposure to Big data technology and NOSQL design and coding with variety of data stores (document, column family, graph, etc.