Data Solutions Engineer: Azure Data Pipelines & ERP Integration

Tech Sales Jobs; Maple Shade Township (NJ); On-site; USD 95,000 - 120,000; Full time

Job summary

RPM Performance Coatings is hiring a Data Solutions Engineer to design and optimize enterprise data pipelines and data products. You will transform and integrate data across ERP systems, Databricks, and Azure, delivering trusted datasets for analytics and operations.

You will collaborate with Data Engineering, BI, and business stakeholders to ensure data quality, governance, and scalability while staying current with cloud data engineering trends.

Qualifications

• Bachelor’s degree in CS/IS/Data Engineering or related field.
• 3–5+ years in data solutions, data integration, or data engineering.
• Proficiency in SQL and modern data management concepts.
• Experience integrating data from ERP systems.
• Strong analytical and problem‑solving skills.
• Knowledge of data governance, security, and quality practices.
• Experience with BI/Analytics teams to deliver trusted data.

Responsibilities

• Design, build, and maintain enterprise data pipelines for ingestion, transformation, and delivery.
• Develop Bronze, Silver, and Gold data layers for business needs.
• Integrate data from ERP and other systems into data platforms.
• Validate data accuracy, completeness, and quality.
• Collaborate with BI and stakeholders to deliver insights.
• Stay current on new data engineering technologies.

Skills

SQL

Data modeling

ETL/ELT

Analytical skills

Problem-solving

Education

Bachelor’s degree in CS/IS/Data Eng

Tools

Databricks

Power BI

Microsoft Fabric

Azure

ERP platforms

Job description

RPM Performance Coatings is hiring a Data Solutions Engineer to design and optimize enterprise data pipelines and data products. You will transform and integrate data across ERP systems, Databricks, and Azure, delivering trusted datasets for analytics and operations.

You will collaborate with Data Engineering, BI, and business stakeholders to ensure data quality, governance, and scalability while staying current with cloud data engineering trends.