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Data Engineer Intermediate Jobs in North Carolina

Data Engineer - Mid Level

Cary, NC · On-site

$107K - $128K/yr

Other duties as assigned Qualifications: * 3 years' experience as a data engineer, business systems ... Intermediate to expert level Excel skills Physical Demands: The physical demands described here are ...

Data Engineer - Mid Level

Cary, NC · On-site

$90 - $120/hr

Other duties as assigned Qualifications: * 3 years' experience as a data engineer, business systems ... Intermediate to expert level Excel skills Physical Demands: The physical demands described here are ...

Senior Software Engineer

Raleigh, NC · On-site

$119K - $157K/yr

Utilizes programming specifications to construct modules, develop testing methods, and design ... Intermediate experience with Change Data Capture (CDC), streaming, and real-time data ingestion ...

What You'll Bring • Strong understanding of cybersecurity and data protection concepts and ... Sales Engineering Skills • Proven ability to deliver compelling demos and technical presentations ...

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Data Engineer Intermediate information

What is a data engineer intermediate?

A Data Engineer Intermediate is a professional who designs, builds, and maintains data pipelines and architectures, typically with a few years of experience in the field. They are responsible for collecting, transforming, and storing data in ways that make it accessible and usable for analytics and business intelligence. Intermediate data engineers often work with tools like SQL, Python, ETL frameworks, and cloud platforms. They collaborate with data scientists, analysts, and other engineers to ensure data quality and optimize data workflows. This role requires a good understanding of data modeling, database systems, and data integration techniques.

What are the key skills and qualifications needed to thrive as a data engineer intermediate?

To thrive as a Data Engineer Intermediate, you need strong programming skills in languages like Python or Java, experience with database systems (SQL/NoSQL), and a solid understanding of data modeling, ETL processes, and data warehousing concepts. Familiarity with tools such as Apache Spark, Hadoop, Airflow, and cloud platforms like AWS or Azure, as well as relevant certifications, is highly valued. Excellent problem-solving abilities, attention to detail, and clear communication skills help set candidates apart in this role. These competencies ensure efficient data pipeline development, reliable data infrastructure, and effective collaboration with data teams and stakeholders.

What are some common challenges data engineer intermediates face when working with large-scale data pipelines?

As a Data Engineer Intermediate, you may frequently encounter challenges related to maintaining data quality and consistency across multiple sources, optimizing ETL processes for performance, and ensuring data pipelines are scalable to handle increasing data volumes. Troubleshooting data latency issues and managing dependencies between data sets are also common hurdles. Collaborating closely with data analysts, data scientists, and other engineers is essential to address these challenges and deliver reliable, high-quality data solutions.

What is the difference between Data Engineer Intermediate vs Data Engineer Junior?

AspectData Engineer IntermediateData Engineer Junior
Required CredentialsBachelor's in CS, experience with SQL, Python, ETL toolsEntry-level, basic knowledge of SQL and scripting
Work EnvironmentCollaborates on complex data pipelines, supports data architectureAssists in data tasks, learns from senior engineers
Employer & Industry UsageUsed in tech, finance, healthcare sectors for data projectsCommon in similar industries as entry-level role
Comparison Search IntentUnderstanding role progression, skills requiredEntry-level position, learning expectations

The main difference between Data Engineer Intermediate and Data Engineer Junior lies in experience, skill level, and responsibilities. Intermediate engineers handle more complex data pipelines and support data architecture, while junior engineers focus on learning foundational skills and assisting senior staff. This distinction helps employers and candidates understand career progression and required competencies.

Can I get a data engineer intermediate job with no experience?

A data engineer intermediate role typically requires prior experience with data pipelines, programming languages like Python or SQL, and familiarity with tools such as Hadoop or Spark. Entry-level positions or internships may be more suitable for those without experience, as intermediate roles generally expect demonstrated skills and some professional background.

What are the most commonly searched types of Data Engineer jobs in North Carolina?

The most popular types of Data Engineer jobs in North Carolina are:

What cities in North Carolina are hiring for Data Engineer Intermediate jobs?

Cities in North Carolina with the most Data Engineer Intermediate job openings:

Infographic showing various Data Engineer Intermediate job openings in North Carolina as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Senior Data Engineer - Credit Data Analytics

Charlotte, NC • On-site

MDAEdge
Custom Software Development Services • 51 - 200 employees

$111K - $134K/yr

Full-time

Re-posted 9 days ago


Job description

Job Summary:
MDAEdge is a company that specializes in data engineering solutions, and they are seeking a Senior Data Engineer to drive data engineering efforts for enterprise-wide capabilities and complex data solutions. The role involves directing code design and delivery tasks, implementing complex data solutions, and collaborating with project management teams to define outcomes.
Responsibilities:
• The Corporate Audit and Credit Review (CACR) analytics & automation team delivers data-driven, risk-based insights and automation solutions to the CACR organization. The Senior Data Engineer role will be responsible for developing and implement a range of analytics and automation solutions, including data extraction, analysis, reporting, and dashboard design, but could include more advanced analytics including statistical analysis, text mining & NLP, and modeling/machine learning/AI. This role demands interaction with highly experienced audit and/or credit professionals, data experts and technology. Intellectual curiosity will drive critical thinking to produce optimal solutions. Strong time management, coordination, communication, and presentation skills are a must in this role.
• Assembles large, complex data sets that meet functional and non-functional requirements, ensuring that the design and engineering approach is consistent across multiple systems.
• Maintains, improves, cleans, and manipulates large data for operational and analytics data systems, builds complex processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, and communicates required information for deployment, maintenance, and support of business functionality.
• Utilizes multiple architectural components in the design and development of client requirements and collaborates with development teams to understand data requirements and ensure the data architecture is feasible to implement.
• Defines and builds data pipelines to enable data-informed decision making, ensuring adherence to release processes and risk management routines
• Contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies any test issues and errors, and leads triage of underlying causes.
• Leads the identification of gaps in data management standards adherence and works with appropriate partners to develop plans to close gaps, leading concept testing and conducting research to prototype toolsets and improve existing processes.
• Mentors Data Engineers in the delivery and release of continuous integration and continuous delivery events and defines key performance indicators and internal controls.
• Utilizes sound, seasoned analytical skills to independently develop analytics & automated testing solutions using a variety of tools (Alteryx, Tableau, etc.) and programming languages (SQL, SAS, Python, etc.)
• Supports the design and execution of new analytics, automated testing tools, and models.
• Responsible for multiple projects simultaneously, ensuring each one is completed on time and efficiently with a high standard of work.
• Coordinates, schedules, scopes, and leads large, cross-functional analytics & automation activities.
• Exercises judgment, critical thinking, and sound communication skills to influence business partners.
• Coaches/trains junior team members in execution of analytics and automation activities.
• This position may also have responsibilities for managing associates. Here all managers at this level demonstrate the following responsibilities, in addition to those specific to the role, listed above.
• Diversity & Inclusion Champion: Models an inclusive environment for employees and clients, aligned to company D&I goals.
• Manager of Process & Data: Demonstrates deep process knowledge, operational excellence and innovation through a focus on simplicity, data-based decision making and continuous improvement.
• Enterprise Advocate & Communicator: Communicates enterprise decisions, purpose, and results, and connects to team strategy, priorities and contributions.
• Risk Manager: Ensures proper risk discipline, controls and culture are in place to identify, escalate and debate issues.
• People Manager & Coach: Provides inspection, coaching and feedback to motivate, differentiate and improve performance.
• Financial Steward: Actively manages expenses and budgets in alignment with objectives, making sound financial decisions.
• Enterprise Talent Leader: Assesses talent and builds bench strength for roles across the organization.
• Driver of Business Outcomes: Delivers results by effectively prioritizing, inspecting and appropriately delegating team work.
Qualifications:
Required:
• Intermediate to advanced knowledge of one or more of the following: SQL, SAS, Alteryx, Python, Tableau or related tools.
• Advanced skills in Microsoft Excel.
• Advanced analytic skills that demonstrate the ability to navigate systems, access data, reconcile numbers from different sources, identify discrepancies and trends, and understand drivers of changes within data.
• Strong track record of implementing automated solutions related to data & analytics, including the ability to extract, organize, and present the data in user-friendly reports, dashboards or tools.
• Ability to work both independently or in teams on multiple projects simultaneously to deliver timely and complete solutions under minimal supervision.
• Strong written and oral communication skills, with ability to communicate with both technical and executive audience.
Preferred:
• Experience with one or more of the following as plus: model development, machine learning/artificial intelligence (AI), and data science.
• Experience with one or more of the following a plus: DataRobot, Instabase, and UIPath.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.