Data Engineer

Divisions Maintenance Group is seeking a Data Engineer to strengthen the Business Intelligence team within Revenue Strategy & Planning. This is an onsite role in Cincinnati, OH, focused on building reliable data infrastructure that supports analytics, reporting, and day-to-day decision-making. You will help deliver dependable datasets through scalable pipelines, strong data quality and governance, and practical partnerships with BI analysts and data scientists.

What You’ll Get

• Health, dental and vision coverage on day 1
• 401K match dollar-for-dollar up to 4% of salary, with immediate 100% vesting
• Paid Primary and Secondary Caregiver leave
• Employee Assistance Program for everyday challenges
• Paid time off to volunteer

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows for analytics and reporting
• Develop and optimize data models in the warehouse to support downstream analytics, BI dashboards, and operational reporting
• Implement orchestration and scheduling for reliable, automated data processing
• Monitor pipeline performance, troubleshoot failures, and support uptime and reliability for critical data systems
• Optimize queries and data structures for performance and cost efficiency
• Establish data quality standards with validation checks and monitoring to ensure accuracy and consistency
• Document data lineage, transformation logic, and schema definitions for transparency and governance
• Partner with stakeholders on data contracts, naming conventions, and architectural standards
• Build reusable frameworks and patterns to improve consistency across datasets
• Collaborate with BI analysts and data scientists to deliver clean, structured datasets
• Support core dimensional models and analytics-ready tables for self-service reporting
• Provide technical guidance on data usage, best practices, and troubleshooting to analytics team members
• Balance platform-level work with responsiveness to evolving business analytics needs
• Use AI tools (for example, ChatGPT and Claude) to accelerate development, documentation, code review, and troubleshooting
• Leverage low-code/no-code automation tools (such as Zapier or Make) when appropriate to streamline workflows and integrations
• Identify opportunities to reduce manual effort through smart automation while maintaining data quality and governance standards
• Build pragmatic solutions that balance technical rigor with speed and business impact
• Other duties as assigned by management

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Computer Engineering, or a related technical field
• 3–5 years of experience in data engineering, analytics engineering, or a related role
• Strong SQL skills, including writing complex queries, optimizing performance, and designing data models
• Experience building and maintaining production data pipelines using modern tools (such as Airflow, dbt, Fivetran, or similar)
• Proficiency in Python for data transformation, automation, and pipeline development
• Working knowledge of cloud data platforms (such as Snowflake, BigQuery, Redshift, or Databricks)
• Familiarity with data modeling best practices (dimensional modeling, normalization, slowly changing dimensions)
• Understanding of data governance principles including lineage, quality monitoring, and documentation
• Experience with Git and CI/CD practices for data workflows
• Comfort using AI tools to accelerate coding, problem-solving, and documentation
• Willingness to use low-code/no-code tools for practical solutions without compromising data integrity
• Ownership-oriented mindset with attention to detail and a focus on reliability
• Ability to manage stress in a fast-paced environment
• Ability to meet the in-person requirements of the team and/or business needs

Tools & Technologies

SQL, ETL/ELT, Airflow, dbt, Fivetran, Python, Snowflake, BigQuery, Redshift, Databricks, Git, CI/CD, ChatGPT, Claude, Zapier, Make