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Divisions Maintenance Group

Data Engineer

Cincinnati, OH, United States

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Job details

Experience: 3–5 years of experience in data engineering, analytics engineering, or a related role.
Posting language: English
Posted: Nov 6, 2026

Original job description

Title: Data Engineer Reports To: Director, Business Intelligence Department: Revenue Strategy and Planning Location: Cincinnati, OH Position Status: Salary Exempt

About DMG:

Divisions Maintenance Group provides facility maintenance services to retail chains and distribution and fulfillment centers across the country.

We are leading the way with our technology, creating world-class products that are revolutionizing the industry and fulfilling our brand promise of “Uninterrupted Peace of Mind.”

DMG is a Certified Great Place to Work with a strong, inclusive culture and top-notch benefits.

Job Summary:

The Data Engineer will join the Business Intelligence team within the Revenue Strategy & Planning organization.

This role focuses on building and maintaining the data infrastructure that powers analytics, reporting, and decision-making across the business. The Data Engineer will design scalable data pipelines, ensure data quality and governance, and support analytics teams with reliable, well-structured datasets. While this role is more technically focused than stakeholder-facing, you’ll partner with BI analysts, data scientists, and technical stakeholders to translate business needs into robust data solutions.

This role is designed for a mid-career engineer with strong technical fundamentals who can own data systems end-to-end, balance platform engineering with analytics enablement, and operate effectively in a fast-moving environment.

What You'll Do:

Data Platform & Pipeline Engineering

Design, build, and maintain scalable data pipelines and ETL/ELT workflows that power 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 ensure uptime and reliability of critical data systems.
Optimize queries and data structures for performance and cost efficiency.

Data Quality & Governance

Establish and enforce data quality standards, validation checks, and monitoring to ensure accuracy and consistency.
Document data lineage, transformation logic, and schema definitions for transparency and governance.
Partner with stakeholders to define data contracts, naming conventions, and architectural standards.
Build reusable frameworks and patterns that improve consistency across datasets.

Analytics Enablement

Collaborate with BI analysts and data scientists to understand requirements and deliver clean, structured datasets.
Support the creation of core dimensional models and analytics-ready tables that enable 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.

Automation & AI-Assisted Workflows

Use AI tools (e.g., ChatGPT, Claude) to accelerate development, documentation, code review, and troubleshooting.
Leverage low-code/no-code automation tools (e.g., Zapier, Make, or similar) to streamline data workflows and integrations where appropriate.
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

Other duties as assigned by management.

What You Need:

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 with experience writing complex queries, optimizing performance, and designing data models.
Experience building and maintaining production data pipelines using modern tools (e.g., Airflow, dbt, Fivetran, or similar).
Proficiency in Python for data transformation, automation, and pipeline development.
Working knowledge of cloud data platforms (e.g., 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 version control (Git) and CI/CD practices for data workflows.
Comfort using AI tools to accelerate coding, problem-solving, and documentation.
Willingness to leverage low-code/no-code tools when they provide practical solutions without compromising data integrity.
Ownership-oriented mindset with attention to detail and a focus on reliability.
Ability to manage the stress of a fast-paced environment.
Ability to meet the in-person requirements of the team and/or business needs.

What You'll Get:

At DMG, you’ll be part of an amazing team that encourages learning, growth, and advancement. Our company has an entrepreneurial spirit that rewards self-starters and encourages employees to take charge of their own careers.

Some of our many benefits include:

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

Divisions Maintenance Group is an equal opportunity employer.

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