Senior Data Engineer

Coric Industries LLC•Southfield, MI

5h•$145,000 - $155,000•Hybrid

About The Position

The Senior Data Engineer is responsible for the design, construction, and operation of the company’s enterprise data warehouse, consolidating data from multiple ERP platforms and supporting business systems across a nationwide, multi-site organization. This position establishes the data architecture, ingestion pipelines, and governed data models that support executive reporting, financial reconciliation, self-service business intelligence, and emerging AI-assisted analytics. As the organization’s first dedicated data engineering hire, the Senior Data Engineer partners closely with finance, sales, and operations leadership to standardize business definitions across acquired companies and to replace manual consolidation processes with reliable, auditable, automated datasets.

Requirements

Bachelor’s degree in computer science, information systems, or a related field required, or equivalent practical experience.
5+ years of progressive data engineering experience, including at least one enterprise data warehouse designed, implemented, and operated in production.
Expert-level SQL, including the ability to profile and reverse-engineer large, undocumented database schemas.
Strong command of dimensional modeling concepts and their practical trade-offs.
Proficiency in Python for pipeline development and automation.
Production experience with at least one modern cloud data platform (e.g., Microsoft Fabric, Azure Synapse, Databricks, Snowflake).
Experience integrating third-party systems via REST APIs.
Experience with data access management (role-based access control, row-level security), data lineage, and audit support.
Proficiency with business intelligence and visualization tools (Power BI or comparable), including semantic model and dataset design, sufficient to support the reporting and analytics teams that build on the warehouse.
Excellent verbal and written communication skills.
Demonstrated ability to gather requirements from non-technical stakeholders, formalize them into documented and governed data definitions, and explain technical trade-offs to senior management.
Ability to manage multiple priorities and meet critical deadlines in a fast-paced environment.
Strong attention to detail and commitment to accuracy.

Nice To Haves

Experience with ERP data environments preferred
Familiarity with Microsoft Dynamics 365 Business Central or dealer management systems a plus.
Experience within equipment distribution, dealership, manufacturing, or related industries preferred.
Familiarity with SOX and IT general controls concepts preferred.

Responsibilities

Design and implement a layered enterprise data warehouse consolidating multiple ERP systems and supporting business applications, including payroll, field service, expense management, and CRM.
Build and operate reliable nightly ingestion pipelines across heterogeneous sources, including relational databases, vendor data exports, REST APIs, and file-based feeds.
Analyze and document legacy ERP database schemas and map them to a canonical, company-wide dimensional model.
Develop and maintain conformed dimensions and fact tables governed by an enterprise data dictionary; participate in structured workshops with business stakeholders to capture and formalize definitions.
Implement automated reconciliation between the data warehouse and existing financial reporting systems, validating accuracy through successive monthly closes to an audit-ready standard.
Design and administer role-based access to warehouse data, including row- and column-level security for sensitive datasets such as payroll and financial records; conduct periodic user access reviews.
Implement and maintain internal controls over the data platform consistent with SOX-aligned IT general controls, including change management, segregation of duties, activity logging, and documented data lineage.
Support internal and external audit activities, responding to inquiries regarding data controls, lineage, access, and reporting accuracy.
Establish and enforce engineering standards, including version-controlled transformations, separate development and production environments, automated data-quality checks, and monitoring and alerting.
Support the business intelligence visualization layer built on the data warehouse, partnering with report developers and business users on semantic models, curated datasets, and dashboard data requirements.
Evaluate data platform technologies and own the platform recommendation and its justification.
Integrate newly acquired companies’ systems into the standardized data architecture as the organization grows.
Produce and maintain documentation of architecture, pipelines, controls, and operational procedures to support long-term maintainability and audit readiness.