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Data Engineer Intermediate Jobs (NOW HIRING)

Guru Schools

Job Title:-Senior Data Engineer

Spring, TX · On-site

$94.30K - $128.10K/yr

Position Title * 61965 - Data Engineer - intermediate to advanced Position Responsibilities Job Title:- Senior Data Engineer Location:- Spring Texas (On-Site) Job Type:- Long Term Contract Market ...

ECS

Software Engineer Intermediate

Washington, DC · On-site

$125K - $165K/yr

Everforth ECS Federal is seeking a TS-cleared Software Engineer Intermediate to support one of our ... Support operations and maintenance of legacy data processes leveraging Python, Java, MS Access, VBA ...

Synaptein Solutions inc

Data Engineer

Atlanta, GA · On-site

$110.10K - $132.20K/yr

Data Engineer Location: Atlanta, GA Duration: 6+Month Contract 5 years of experience with at least ... Intermediate Business modeling skills using Excel or BI Tool Excellent oral, written, and ...

Synaptein Solutions inc

Data Engineer

Atlanta, GA · On-site

$110.10K - $132.20K/yr

Data Engineer Location: Atlanta, GA Duration: 6+Month Contract 5 years of experience with at least ... Intermediate Business modeling skills using Excel or BI Tool Excellent oral, written, and ...

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Data Engineer Intermediate information

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$44.5K

$129.7K

$177.5K

How much do data engineer intermediate jobs pay per year?

As of May 29, 2026, the average yearly pay for data engineer intermediate in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Engineer Intermediate, and why are they important?

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 are Data Engineer Intermediates?

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 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.

What cities are hiring for Data Engineer Intermediate jobs? Cities with the most Data Engineer Intermediate job openings:
What are the most commonly searched types of Data Engineer jobs? The most popular types of Data Engineer jobs are:
What states have the most Data Engineer Intermediate jobs? States with the most job openings for Data Engineer Intermediate jobs include:
Data Engineer Intermediate jobs near you
Data Engineer (Intermediate or Senior)

Data Engineer (Intermediate or Senior)

Teacher Retirement System of Texas

Austin, TX • On-site

$118.70K - $142.60K/yr

Other

Posted 26 days ago

Job description

The Data Engineer is responsible for designing, developing, and optimizing data pipelines, data modeling, and platform management to support seamless integration and operation of data systems. The incumbent will maintain the data warehouse, generate complex reports, and perform in-depth data analysis, while actively contributing to Agile team activities. This position will proactively collaborate with the Data Engineering Team, IT staff, other enterprise stakeholders and agency employees.

The Data Engineer Senior is responsible for designing, developing, architecting, and enhancing data platforms and pipelines, ensuring robust data models and system integrations for enterprise operations. The incumbent will oversee advanced data warehouse maintenance, drive strategic data initiatives, and perform comprehensive analysis while actively contributing to Agile team activities. This position will proactively collaborate with the Data Engineering Team, IT staff, other enterprise stakeholders, and agency employees.

In addition to the above, the Data Engineer will have expertise in DevOps principle and experience in CI/CD, Azure services, Kubernetes, and scripting skills (SQL, Python, PowerShell), along with testing automation. Terraform knowledge and Azure certifications are preferred.
 
WHAT WILL YOU DO
Data Engineering
Develop and manage data platforms.
Design and implement ETL processes and perform basic data lake management.
Implement and manage CI/CD pipelines with intermediate proficiency.
Create and maintain basic data models to ensure structured data storage and accessibility.
Manage data catalogs to maintain an organized and easily accessible repository of data resources.
Develop and maintain data warehouses.
Perform administrative tasks and assist in basic system administration duties, contributing to the overall management and upkeep of data systems.
Manage data permission, ensuring proper access control and data security.
Contribute to the maintenance and optimization of the data warehouse, ensuring data integrity and availability.
Develop data-driven applications, contributing to the creation of data solutions that support business needs.
Conduct data analysis and assist in larger data analysis projects, providing insights and support to business stakeholders.
Engage in scrum activities and actively participate in Agile methodologies.
Generate reports using reporting tools, and provide support in more advanced reporting tasks as required.
Collaborate with stakeholders to gather requirements and contribute to defining project scopes and objectives.
Develop visually appealing and intuitive dashboards that provide visibility into key performance, risk, and control indicators across agency divisions and departments.
Performs related work as assigned. 
Data Engineering Senior  
Develop and manage data platforms.
Design and maintain ETL processes and perform advanced data lake management.
Oversee and manage the implementation of CI/CD pipelines utilizing advanced DevOps practices.
Create and maintain advanced data models to ensure structured data storage and accessibility.
Enhance data catalogs to maintain an organized and easily accessible repository of data resources.
Enhance the efficiency of data warehouses and oversee complex warehousing.
Optimize system performance and manage complex systems, improving ease of management and reliability of systems.
Maintain complex data permissions, ensuring proper access control and data security.
Improve the maintenance and optimization of data warehouses, ensuring data integrity and availability.
Develop data-driven applications, contributing to the creation of data solutions that support business needs.
Conduct advanced data analysis and lead larger data analysis projects, providing insights and support to business stakeholders.
Lead scrum activities, ensuring team adherence to Agile practices.
Automate reports using reporting tools and provide support for more advanced reporting tasks as required.
Partner with stakeholders to align data strategies with business goals.
Develop visually appealing and intuitive dashboards that provide visibility into key performance, risk, and control indicators across agency divisions and departments.
Performs related work as assigned. 

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