Data Engineer

Ridgemont Resources, Inc.; Pittsburgh (Allegheny County); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Ridgemont Resources, Inc. seeks a Data Engineer to build ETL/ELT pipelines and an analytics-ready warehouse. You will integrate Oracle, Ross ERP, Dynamics 365, and other systems, writing optimized SQL and scripts for reliable reporting. Work closely with BI and business stakeholders to ensure data quality and governance.

You will be based on-site in Pittsburgh with two remote days per month after ramp-up, contributing to manufacturing-focused data initiatives.

Qualifications

• 5+ years in data engineering, ETL development, or related role.
• Strong hands-on SQL development and performance tuning.
• Experience with Oracle databases and data warehousing fundamentals.
• Ability to troubleshoot pipeline failures with minimal direction.
• Bachelor’s degree or equivalent professional experience.

Responsibilities

• Design, build, and optimize ETL/ELT pipelines feeding an enterprise data warehouse.
• Integrate data from Oracle, Ross ERP, Microsoft Dynamics 365 Finance & Operations, and other systems.
• Write and tune complex SQL queries, stored procedures, and scripts for performance and reliability.
• Monitor data loads, diagnose failures, and resolve discrepancies independently.
• Strengthen data quality through validation, logging, and error handling.
• Partner with BI developers, analysts, and business stakeholders to deliver trusted reporting data.
• Document data flows and transformation logic; contribute to warehouse architecture and code reviews.

Skills

SQL development

Performance tuning

ETL/ELT fundamentals

Oracle databases

Troubleshooting data pipelines

Education

Bachelor's degree in related discipline

Tools

WhereScape RED

TimeXtender

Microsoft Fabric

Dataverse

SSIS

Informatica

Power BI

Job description

Data Engineer

Build the Data Foundation Behind Smarter Decisions

Pittsburgh, PA | Full-Time | Primarily On-Site

Our client is seeking a hands-on Data Engineer who loves turning complex, disconnected data into reliable intelligence. This is an opportunity to make a visible impact on a growing industrial organization—building the pipelines and warehouse foundations that power meaningful reporting and better business decisions.

Why This Opportunity Stands Out

Own critical data pipelines from source systems to analytics-ready datasets.

Work closely with a business intelligence team on high-impact reporting initiatives.

Bring your SQL and Oracle expertise to real operational challenges in a manufacturing-oriented environment.

What You’ll Do

Design, build, and optimize ETL/ELT pipelines feeding an enterprise data warehouse.

Integrate data from Oracle, Ross ERP, Microsoft Dynamics 365 Finance & Operations, and other systems.

Write and tune complex SQL queries, stored procedures, and scripts for performance and reliability.

Monitor data loads, diagnose failures, and resolve discrepancies independently.

Strengthen data quality through validation, logging, and error handling.

Partner with BI developers, analysts, and business stakeholders to deliver trusted reporting data.

Document data flows and transformation logic; contribute to warehouse architecture, dimensional modeling, and code reviews.

What You Bring

5+ years in data engineering, ETL development, or a closely related role.

Strong hands-on SQL development and performance-tuning skills.

Experience with Oracle databases and sound ETL/ELT and data warehousing fundamentals.

Ability to troubleshoot pipeline failures and data accuracy issues with minimal direction.

Bachelor’s degree in a related discipline or equivalent professional experience.

Extra Experience We’d Love to See

WhereScape RED or TimeXtender; Microsoft Fabric, Lakehouse, or Dataverse.

D365 Finance & Operations, SSIS, Informatica, Power BI, or DBA experience.

Dimensional modeling and manufacturing, mining, or industrial data environments.

Work Arrangement

This position is based on-site in Pittsburgh, with two remote days per month available after the initial ramp-up period.