Data System Engineer

Ampcus - Alpharetta, GA

Full-time

Alpharetta, GA

Professional, Scientific, and Technical Services

About the position

The Data System Engineer at Ampcus, Inc. will play a crucial role in the development and management of data systems that support both on-premise and cloud-based platforms, specifically utilizing AWS and Azure. This position requires a highly motivated individual who is capable of handling various tasks related to data engineering, data modeling, ETL processes, data warehousing, and data analytics. The successful candidate will be responsible for establishing, modifying, and maintaining data structures and associated components according to design specifications. They will also be expected to understand and document business data requirements effectively. In this role, the Data System Engineer will create both Conceptual and Logical Data Models at the Enterprise and Business Unit/Domain levels. A strong understanding of XML/JSON, schema development, database concepts, and designs is essential. The engineer will collaborate with Senior Data Engineers and Senior Data Architects to develop platform-level data models and database designs. Participation in reviews of their own work and that of colleagues is expected to ensure quality and adherence to standards. The Data System Engineer will also need to have a working knowledge of core tools used in planning, analyzing, designing, building, testing, configuring, and maintaining assigned applications. They will participate in the software delivery methodology of the assigned team, which may include Agile, Scrum, Test-Driven Development, or Waterfall, to support the development of data engineering pipelines. Additionally, the engineer should understand infrastructure technologies and components, including servers, databases, and networking concepts. Writing code to develop, maintain, and optimize batch and event-driven processes for managing and analyzing large volumes of structured and unstructured data is a key responsibility. The role also involves metadata integration in data pipelines and automating build and deployment processes using Jenkins to enable faster, high-quality releases.

Responsibilities

• Responsible for data engineering, data modeling, ETL processes, data warehousing, and data analytics & science.
• Establish, modify, or maintain data structures and associated components according to design.
• Understand and document business data requirements.
• Develop Conceptual and Logical Data Models at Enterprise and Business Unit/Domain Level.
• Understand XML/JSON and schema development/reuse, database concepts, and Open Source and NoSQL concepts.
• Collaborate with Sr. Data Engineers and Sr. Data Architects to create platform-level data models and database designs.
• Participate in reviews of own work and colleagues' work.
• Utilize core tools for planning, analyzing, designing, building, testing, configuring, and maintaining assigned applications.
• Participate in assigned team's software delivery methodology (Agile, Scrum, Test-Driven Development, Waterfall, etc.) in support of data engineering pipeline development.
• Understand infrastructure technologies and components like servers, databases, and networking concepts.
• Write code to develop, maintain, and optimize batch and event-driven processes for managing and analyzing large volumes of structured and unstructured data.
• Integrate metadata in data pipelines.
• Automate build and deployment processes using Jenkins across all environments.

Requirements

• Up to 4 years of software development experience in a professional environment.
• Understanding of Agile or other rapid application development methods.
• Exposure to design and development across one or more database management systems such as DB2, SybaseIQ, Snowflake.
• Exposure to methods relating to application and database design, development, and automated testing.
• Understanding of big data technology and NoSQL design and development with a 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.
• Experience with cloud technologies such as AWS and Azure, including deployment, management, and optimization of data analytics & science pipelines.
• Bachelor's degree in computer science, computer science engineering, or related field required.

Nice-to-haves

• Collibra
• Terraform
• Java
• Golang
• Ruby
• Machine Learning Operation deployment