Data Engineer
Consumers Energy
Consumers Energy is Michigan’s largest energy provider, providing natural gas and/or electricity to 6.8 million of the state’s 10 million residents in all 68 Lower Peninsula counties. Consumers Energy knows job number one is to keep the lights on for customers. We are committed to delivering reliable, clean, and affordable energy to our customers 24/7. This position is not eligible for immigration sponsorship, e.g., H-1B, TN, etc. Please do not apply if you will need immigration sponsorship for a work visa now or in the future, including sponsorship for H-1B, TN, etc., now or in the future. We are unable to hire individuals with CPT, OPT, or STEM OPT for this position as the position is not eligible for participation in the H-1B lottery program and is not eligible for current or future immigration sponsorship for a work visa. Location : This is a hybrid (virtual/onsite) position with required onsite days on Monday, Tuesday and Thursday assigned to One Energy Plaza located in Jackson, MI. The selected candidate must be within a commutable distance or willing to relocate (relocation package is available for those that qualify). General Summary of Job Responsibilities The Data Engineer is responsible for partnering with analytics teams and business stakeholders across the enterprise to gather data requirements and design, develop, and maintain data pipelines and architectures in accordance with established IT standards and best practices. This role supports the development of data warehouses, data extraction and loading processes, data models, testing strategies, and application performance optimization. The Data Engineer will build analytical tools, assemble and prepare large and complex datasets, design and develop ETL solutions using various technologies, create data visualizations, and identify opportunities to automate manual data preparation processes. Additionally, this role focuses on improving data quality, optimizing system performance, and ensuring the reliability and scalability of data solutions. Guidance from Senior and Principal Data Engineers, as well as Data Architects, will be sought as needed. Essential Duties and Responsibilities Gather and evaluate requirements provided by Data Architects and business stakeholders; assess development alternatives and establish project timelines. Assemble, cleanse, and prepare large and complex datasets from multiple data sources to support business requirements for small and large-scale enhancements. Collaborate with business partners, stakeholders, and IT teams to design and develop efficient, scalable data pipelines. Develop data visualizations and reporting solutions that provide customer insights, operational efficiencies, and key business performance metrics. Identify opportunities to automate manual data preparation and transformation processes, improve data quality, and optimize system performance. Prepare technical documentation and project artifacts that support solution development and project deliverables. Provide technical guidance and support for solution design, testing, documentation, and implementation activities. Support incident management processes and provide technical consulting and production support for existing applications and solutions. Perform other duties as assigned. Knowledge/Skills/Abilities Excellent verbal and written communication skills with the ability to effectively interact with all levels of the organization. Demonstrated ability to establish and maintain productive working relationships with business and IT teams. Knowledge of project planning and full software development lifecycle delivery using Agile methodologies. Understanding of data testing methodologies, quality assurance practices, and testing tools. Ability to collaborate effectively with contractors, consultants, vendors, and cross-functional teams. Understanding of database management principles and methodologies, including data structures, data modeling, data warehousing, and transaction processing. Knowledge of data design principles, methodologies, and best practices, including concepts such as structured design, scalability, reliability, maintainability, supportability, and survivability. Familiarity with change management, release management tools, and deployment processes across multiple technologies and teams. Education/Experience Bachelor's degree in computer, engineering, data sciences or related field with two (2) or more years of data engineering or software engineering experience. Beginner level experience with analytic tool build, data architecture/design, user requirements definition, build BIG data pipeline, understanding of ETL tool extraction, basic data testing aptitude, and understanding of analytic tool deployment processes and best practices.
- OR] Associate's degree in computer, engineering, data sciences or related field with four (4) or more years of data engineering or software engineering experience. Beginner level experience with analytic tool build, data architecture/design, user requirements definition, build BIG data pipeline, understanding of ETL tool extraction, basic data testing aptitude, and understanding of analytic tool deployment processes and best practices.
- OR] High School Diploma/GED with six (6) or more years of data engineering or software engineering experience. Beginner level experience with analytic tool build, data architecture/design, user requirements definition, build BIG data pipeline, understanding of ETL tool extraction, basic data testing aptitude, and understanding of analytic tool deployment processes and best practices.
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