Data Engineer
Monroe, NCJob$55–62/hrSeen todaySeen in employer's feed today
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At a glance
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Job overview
The Data Engineer shapes enterprise data strategy and architecture while building and maintaining modern data solutions, including pipelines, databases, warehouses, and lakehouses. The role combines strategic oversight with hands-on technical delivery to support scalable, reliable, efficient systems aligned with organizational goals. It uses T-SQL, Azure SQL, Azure Data Factory, Microsoft Fabric, and ETL/ELT practices to guide modernization and support data-driven decision-making.
Skills & qualifications
Skills
Qualifications
Full job description
Job Description
On-Site 5 days per week
The Data Engineer is responsible for shaping our clients enterprise data strategy and architecture while also contributing hands-on expertise in building and maintaining modern data solutions (pipelines, databases, warehouses, lakehouses, etc). This role blends strategic oversight with technical delivery, ensuring that data systems are scalable, reliable, efficient, and aligned with organizational goals. The associate will leverage advanced knowledge of T-SQL, Azure SQL, Azure Data Factory, Microsoft Fabric, and ETL/ELT best practices to design robust solutions, guide modernization efforts, and support data-driven decision-making across the business in a fast-paced environment with lots of autonomy
Pay Rate: $55-62/hr
Skills and Requirements
Bachelor of Science in Computer Science, Bachelor of Arts in Information Systems, or relevant work experience required
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3-4 years of experience in data architecture and engineering roles · Advanced proficiency in T-SQL
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Effective at Azure SQL database design and optimization
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Proven experience developing and maintaining pipelines with Azure Data Factory
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Expertise with Microsoft Fabric for advanced data integration and analytics
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Strong understanding of data modeling, schema design, and warehousing techniques
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Experience with ETL/ELT processes and performance tuning
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Working proficiency in Python, including PySpark, for data transformation in Fabric notebooks
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Demonstrated ability to set and enforce data governance and architecture standards
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Knowledge of Power BI (semantic models, DAX) or similar BI tools preferred
Microsoft Certified: Fabric Data Engineer Associate (DP-700), Fabric Analytics Engineer Associate (DP-600), or comparable Azure data certification preferred
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to [email protected].
How this job compares
Set against the 6,440 open Data Engineer jobs on Olive Jobs, counted November 14, 2026.
- Pay
- This posting$55–62/hr
- US median$60–73/hr260 hourly ranges
This range's midpoint, $58.50/hr, is 13% below the US median midpoint ($67/hr) — in the middle half of Data Engineer hourly ranges across the US.
- Openings
- Olive Jobs lists 184 open Data Engineer jobs in North Carolina and 6,440 across the US. 8% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 3 years of experience; Data Engineer postings that state a minimum ask for 5 years at the median (5,680 postings).
- Education
- 2,477 of the 6,440 open Data Engineer jobs (38%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 14, 2026. Figures based on too few postings are left out.
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