Senior Data Engineer - Sharonville, OH Corporate Headquarters

DuBois Chemicals•Sharonville, OH

14d•Onsite

About The Position

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. POSITION SUMMARY: The Senior Data Engineer will work onsite at our Corporate Headquarters in Sharonville, OH. The Senior Data Engineer is responsible for the design, development, and operation of DuBois Chemicals’ data pipelines to support enterprise analytics, reporting, and AI initiatives. This role plays a critical part in transforming transactional and unstructured data into trusted, analytics‑ready datasets that enable informed decision‑making across Sales, Manufacturing, and Finance. This is a hands‑on, senior individual contributor role requiring deep technical expertise, strong collaboration skills, and the ability to operate in a fast‑paced environment. The Senior Data Engineer partners closely with analytics, BI, and business stakeholders to ensure data assets are scalable, governed, reliable, and aligned to business needs.

Requirements

3-5 years of technical, hands-on experience as a Data Engineer working with both transactional and analytical data.
Deep understanding of dimensional data modeling.
Demonstrated experience transforming ERP and CRM data into analytics‑ready datasets.
Hands‑on experience with modern cloud‑based data platforms and data pipeline development: ADF, dbt, snowflake.
Strong SQL and Python.
Ability to manage multiple priorities, meet deadlines, and collaborate effectively with technical and non‑technical stakeholders.
Strong written and verbal communication skills.
Candidates will ideally live within a reasonable daily commute of Sharonville, OH, or be willing to relocate at own expense

Nice To Haves

Experience with Microsoft Dataverse, OneLake
Experience developing analytics solutions for Power BI.
Familiarity with building custom agents using Copilot Studio or Azure AI Foundry.
Exposure to Snowflake Cortex or similar AI‑enabled data platform capabilities.

Responsibilities

Data Engineering & Analytics Enablement Design and implement well‑structured dimensional data models (fact and dimension tables; star schemas) from unstructured and transactional data, with an initial focus on Dynamics 365 ERP and CRM systems.
Translate business requirements into governed, reusable data models by moving business logic out of dashboards and into the data layer.
Deliver analytics‑ready datasets consumed by Power BI and downstream analytics and AI use cases.
Establish standardized metrics, definitions, and grains to ensure consistency, accuracy, and trust across enterprise reporting.
Design, build, and operate reliable ingestion and transformation pipelines across multiple data sources.
Translate existing Alteryx workflows into reusable, performant data transformations.
Integrate data pipeline with Microsoft Fabric and Azure services as appropriate, including Azure Data Factory, Azure Data Lake Storage, and Event Hubs.
Data Quality, Metadata & Reliability Enrich datasets with technical and business metadata, including data definitions, ownership, and lineage.
Implement data quality monitoring and controls, including freshness, duplicate detection, schema drift, and anomaly detection.
Improve pipeline observability, monitoring, and operational reliability to support production‑grade data workloads.
Collaboration & Technical Leadership Partner closely with analytics engineers, BI developers and business stakeholders to deliver trusted data solutions.
Contribute to shared standards, patterns, and best practices for data engineering and analytics enablement.
Provide technical leadership and mentorship appropriate for a senior, hands‑on engineering role without direct people management responsibilities.