Senior Data Engineer – Snowflake & dbt for Analytics

CBTS; Sharonville (OH); On-site; USD 110,000 - 150,000; Full time

Job summary

DuBois Chemicals seeks a Data Engineer to design, develop, and operate scalable data pipelines for analytics, reporting, and AI initiatives. You will transform transactional and unstructured data into analytics-ready datasets used by Sales, Manufacturing, and Finance.

This senior, hands-on role requires deep technical expertise and collaboration with analytics, BI, and business stakeholders to ensure data assets are scalable, governed, and reliable.

Qualifications

• 3–5 years as Data Engineer handling transactional and analytic data.
• Deep expertise in Snowflake architecture, performance, and modeling.
• Strong experience with dbt including development, testing, and deployment.
• Experience integrating data from ERP/CRM/operational systems (Dynamics 365 preferred).
• Ability to manage multiple priorities and communicate with technical and non-technical stakeholders.

Responsibilities

• Design and implement scalable dimensional data models (fact/dim tables, star schemas).
• Maintain enterprise standards for data modeling, naming, transformations, and reusable logic.
• Partner with stakeholders to define metrics, hierarchies, and master data concepts.
• Develop analytics-ready data products for Power BI and AI solutions.
• Ingest data across sources and maintain dbt transformation frameworks.
• Optimize Snowflake performance and cost; implement CI/CD for data transformations.

Skills

Dimensional data modeling

Snowflake architecture

dbt development

Data integration

Stakeholder collaboration

Data quality & lineage

Education

Bachelor’s degree in CS/IT/Engineering

Tools

Snowflake

dbt

Job description

DuBois Chemicals seeks a Data Engineer to design, develop, and operate scalable data pipelines for analytics, reporting, and AI initiatives. You will transform transactional and unstructured data into analytics-ready datasets used by Sales, Manufacturing, and Finance.

This senior, hands-on role requires deep technical expertise and collaboration with analytics, BI, and business stakeholders to ensure data assets are scalable, governed, and reliable.