Data Architect; Databricks Data Engineer

For more than 50 years, NISC has worked to develop technology solutions for our customers, who we call our “Members”. Those Members are comprised primarily of 960+ utilities and broadband across North America. Our mission is to deliver technology solutions and services that are Member‑focused, quality driven and valued priced. Our Members have over 16 million end customers (residential and businesses who receive power, internet, television and/or telephone services) that our enterprise software solution enables our Member's employees to compete effectively in the industry, while excelling in providing customer service to their end customers.

NISC exist to serve our Members and help them serve their communities through our innovative software products, services and outstanding customer support.

We are seeking an experienced Data Engineer to join our growing team of data analytics experts. The hire will be responsible for curating and optimizing our data and data pipeline architecture in Databricks
, as well as optimizing data flow and collection for various application teams. The Data Engineer will support our application experts, software developers, database architects, and data analysts on a Data Roadmap strategy and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be comfortable supporting the data needs of multiple teams, systems, and products. We look for individuals who will thrive in a team environment, be committed to accomplishing a common goal and excited by the prospect of optimizing or even re‑designing our company’s data architecture and have some fun along the way.

• Hybrid from one of our office locations:
  • Cedar Rapids, IA
  • Lake Saint Louis, MO
  • Mandan, ND
• Hybrid
  
  Schedule:
  
  Minimum of working 3 day per week out of an office location and ability to work up to all 5 days a week from an office location.
  • Required Days from an Office
    
    Location:
    
    Tuesday and Wednesday - the third required day will be up to the candidate and their supervisor to choose.
• Virtual Office: Candidates working from a remote location within approved states will be considered for those who have applicable industry experience with Databricks.

• Assemble large, complex data sets that meet functional / non‑functional business requirements.
• Understanding of Data Warehouse and Data Lakehouse paradigms.
• Design and build optimal data pipelines from a wide variety of data sources using AWS and Databricks technologies.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data‑related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing a unified data stream.
• Work with other data engineering experts to strive for greater functionality while making data more discoverable, addressable, trustworthy, and secure.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re‑designing infrastructure for greater scalability, etc.
• Create and maintain a culture of engagement and one that is conducive of NISC’s Statement of Shared Values.
• Commitment to NISC’s Statement of Shared Values.

• Experience building and optimizing data pipelines, architectures, and data sets.
• Hands‑on experience developing and optimizing data pipelines and workflows using Databricks.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build ETL processes supporting data transformation, data structures, metadata, dependency, and workload management.
• Working knowledge of message queuing, stream processing, and highly scalable data stores.
• Experience supporting and working with cross‑functional teams in a dynamic environment.
• Candidate with experience in a Data Engineer role, who has attained a BS or MS degree in Computer Science, Statistics,…