Data Engineer

Join the diverse and dynamic team that powers Michigan's largest energy provider and one of the nation's largest gas and electric combination utilities.  Consumers Energy services 6.8 million of Michigan's 10 million residents - caring for our friends and neighbors in all 68 Lower Peninsula counties.  We embrace a cleaner and leaner utility vision focused on eliminating energy waste and adding renewable energy from sources such as wind and solar.

LOCATION: The successful candidate will be expected to work in a hybrid status of reporting to any Consumers Energy Service Center every Monday, Tuesday, and Thursday with home office flexibility on Wednesday and Friday.

GENERAL SUMMARY OF JOB RESPONSIBILITIES:

The Data Engineer will be responsible for partnering with various analytic teams and business partners throughout the enterprise to collect data requirements and design and build data pipelines/architecture as per IT best practices defined. Creating a data warehouse, design-related extraction, loading data functions, testing designs, data modeling, and ensure the smooth running of applications. Building analytic tools, assembling and cleaning BIG data, designing and building ETL using various technology languages, creating data visualization, assembling large data and identifying and improving internal process to automate manual data wrangling, optimizing performance, and improve data quality. Seek guidance from Senior/Principal Data Engineers and Data Architects as needed.
 

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Design Kimball based dimension and fact tables based on business requirements. New designs must contribute to  the overall team data model if applicable
• Assemble and clean BIG data; data sets including various data sources to meet functional business requirements for small to large enhancements
• Capture/evaluate requirements from the data architect or business partner
• Consider development alternatives, and establish timelines
• Create data visualizations for customer insight, operational efficiency and other key business performance metrics using various reporting tools
• Identify opportunities to improve internal process to automate manual data wrangling, optimizing performance, and improve data quality
• Prepare artifacts to support solutions as well as to document activities as part of a project
• Provide incident management and direct technical consulting and support for current applications/solutions
• Provide technical guidance for small to large enhancements in areas of solution alternatives, design, testing and documentation
• Work with Various Stakeholders/IT to design and build efficient data pipelines for small to large enhancements
• Other duties as assigned or may be necessary

KNOWLEDGE/SKILLS/ABILITIES:

• Knowledge of project planning/full lifecycle delivery using Agile framework, preferably using ADO
• Understanding of data test methodologies and testing tools
• Understanding of database management principles and methodologies, including data structures, data modeling, data warehousing and transaction processing
• Proficiency in Python, SQL and Kimball design concepts must be demonstratable
• Knowledge of data design principles (dimension/fact), methods and approaches
• Able to apply systems engineering concepts such as: data structured design, supportability, survivability, reliability, scalability and maintainability
• Ability to work effectively with contract employees and vendors
• Knowledge of change and release tools and processes utilized to implement solutions across multiple teams and technologies
• Knowledge of data design principles, methods, and approaches, applying systems engineering concepts such as: data structured design, supportability, survivability, reliability, scalability, and maintainability
• Knowledge of project planning/full lifecycle delivery using Agile framework
• Must have excellent verbal and written communication skills and be able to work with all levels of the organization
• Proficient in establishing and maintaining good working relationships (business and IT teams)
• Understanding of data test methodologies and testing tools
• Understanding of database management principles and methodologies, including data structures, data modeling, data warehousing, and transaction processing
   

EDUCATION/EXPERIENCE:

• Bachelor’s degree in computer, engineering, data sciences or related field with two (2) or more years of Software Engineering experience including 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 required

PREFERRED SKILLS:

• Experience with Python, SQL, ADF, DBT and Databricks