Data Engineer

SHI International Corp.•US - TX - Home Office, TX

13d•$120,000 - $160,000•Hybrid

About The Position

SHI One is an exciting team within the Advanced Solutions Group of SHI that is building new digital experiences for our internal users, customers and partners. The Engineer will be responsible for the analysis, design, and development of solutions focused on data engineering and ETL workflows. As a Data Engineer, you will work with customers and internal stakeholders to understand their business needs and help them achieve outcomes with your solutions and guidance. You will research all data sources concerning business operations and be responsible for outlining designs to integrate, centralize, and maintain the data. You will help to establish a new data engineering practice and be a technical leader within the Product organization.

Requirements

Completed Bachelor’s Degree in Computer Science or a related field, or relevant work experience
5+ years of experience in a similar role
5+ years of experience using Python and SQL required
Ability to travel 10%
The ability to understand and utilize cloud computing technologies, including virtualization, IaaS, PaaS, and SaaS delivery models, to implement and manage scalable cloud solutions. - Intermediate
The ability to write, debug, and maintain code in various scripting and programming languages to automate tasks and develop software solutions. - Intermediate
The ability to define, design, build, and maintain robust systems and solutions by leveraging systems and infrastructure effectively. - Intermediate
The ability to systematically identify, document, and manage the technical needs and specifications of a project by engaging with stakeholders and analyzing business objectives to ensure successful project outcomes. - Intermediate
Proficiency in implementing and managing DevOps practices, including continuous integration, continuous delivery, infrastructure as code, and monitoring to enhance the collaboration between development and operations teams - Intermediate
Proficiency in using SQL for database management, including tasks such as querying, updating, and managing relational databases to efficiently handle data retrieval and manipulation - Intermediate
Proficiency in utilizing Platforms as a Service (PaaS) for deploying, managing, and scaling applications, including tasks such as application hosting, database integration, and development tool support; Microsoft Azure or Amazon Web Services highly preferred - Intermediate
Proficiency in using Object-Relational Mapping (ORM) frameworks for database interaction, including tasks such as mapping objects to database tables, managing database schemas, and performing CRUD operations efficiently - Intermediate
Proficiency in using Test-Driven Development (TDD) methodologies, including tasks such as writing automated test cases before code implementation, ensuring code quality, and facilitating continuous integration and deployment - Intermediate

Nice To Haves

5+ years of experience using C# and/or Java preferred

Responsibilities

Design, develop, and implement scalable data pipelines and software solutions to support data engineering and analytics needs.
Collaborate with stakeholders, including data engineers, data scientists, and AI engineers, to build and deploy enterprise-scale data analytics solutions.
Analyze business requirements and transform raw data into reusable analytics assets using modern data platforms and tools.
Implement best practices for data quality, version control, and deployment within analytics platforms to ensure data accuracy and accessibility.
Troubleshoot, identify, and resolve software and data-related issues, providing fixes and continuous improvements.
Partner with solution architects to ensure seamless integration of analytics solutions into broader architectural designs.
Develop and maintain comprehensive documentation for software and data processes, ensuring effective knowledge sharing.
Conduct data analysis to support data-driven decision-making and assist in resolving data-related issues.
Support software design and development processes, including creating development environments and testing frameworks.
Collaborate with business units and engineering teams to develop and execute a long-term data platform architecture strategy.