Location: Cincinnati

Hybrid Schedule: 3 days in office / 2 days at home weekly 

Job Summary  
As a Sr. Data Modeler on the team, you will report to the Director of Data Engineering. The Data Modeler is responsible for developing, updating, and enhancing data models and semantic layer to support reporting, data visualization, business intelligence, and data science. As a Data Architecture expert, the Data Modeler will be an integral member of the Data Engineering organization collaborating with multiple Agile squads to build and deploy advanced SQL queries following best practices from Inmon and Kimball.

You will work in a highly collaborative lean Agile environment to build and continuously improve our data models in addition to using your technical experience and expertise for data analysis to support recommendations along with judgment to make decisions or solve moderate to complex tasks or problems. 

What You’ll Do 

• Design and build within a modern data architecture using Snowflake and Atlan along with other tools to add product features for each ART. Your data models and robust semantic layer will support visualizations, business intelligence, and data science. 
• Clearly communicate solutions to both technical and non-technical team members.
• Responsible for enforcing the Data Modeling and Data Architecture standards across the Data and Analytics organization.
• Advanced SQL query development experience required. 
• Responsible for Metadata Management using Atlan and Snowflake to define, govern, and manage metadata for our data product. Must have expertise with metadata repositories, this role will build and maintain the integrity of our data product semantics and glossary.  
• You will manage and update the enterprise data architecture artifacts, Data glossaries, data architecture, data flows, and processes. 
• Communicate daily with team members regarding product features, development progress and barriers. 
• Translate business problems into data solutions and connect to business impact. 
• Apply defined best practices to the development and support of our Data Warehouse, relational structures, dimensional data modeling and structured query language (SQL) skills. 
• Evaluate and recommend new data management technologies and tools. 
• Optimize data architecture for performance, cost, and efficiency. 
• You will be challenged to be innovative in your approach to integrate, secure and scale data from multiple internal and external data sources while reducing technical debt. 

What We Need 

• 4+ years of experience in data modeling.
• 4+ years focusing on cloud-based solutions. 
• Experience in developing data models, data integration processes, and data flows on cloud platforms.
• Understanding of Kimball Data Warehousing design principles, Unified Star Schema (USS) or Data Vault.
• Firsthand experience in building large scale data warehousing solutions on Snowflake. 
• Experience developing dimensional data models and semantic data layer. 
• Hands-on experience in relational and multi-dimensional data modeling, including multiple source systems from databases and flat file.
• Proven experience implementing complex stored procedures along with an understanding of standard DWH and ELT concepts. 
• Effective Communication Skills both written and verbal within all levels of the organization. 
• Familiarity with machine learning and Data Science technologies their unique data requirements 
• Ability and willingness to work within a lean Agile team to translate needs of our business partners into product features which enhance our self-service data platform.  
• Proven experience delivering within a distributed team. 

Desired Qualifications 

• Bachelor’s degree in computer science or a related field 
• You have experience with various patterns of data ingestion, processing, and curation. 
• Experience with Looker preferred. 
• Experience implementing data quality initiatives such as test harnesses, monitoring, and auditing features on data. 
• Experience with CI/CD workflows using GitHub preferred. 
• Experience with Redshift, Treasure Data or Microsoft Azure is helpful 
• Build/Design data pipeline using Python/Snowflake/Airflow preferred. 
• Experience with AWS data storage and management technologies such as S3 
• Familiarity with orchestration technologies (e.g., Airflow, Astronomer) 
• First-hand experience with Airflow. 

What You’ll Need to Succeed 

• A team player with a solid work ethic with the ability to collaborate productively with a distributed team. 
• Innovative and Solution-oriented mindset along with a positive attitude 
• Strong business acumen and problem-solving competency 

#LI-ED1 #LI-Hybrid