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Data Engineer Intermediate Jobs (NOW HIRING)

Data Engineer

Baltimore, MD · Remote

$116K - $139K/yr

Microsoft Azure SQL (Intermediate proficiency) * Experience building and deploying data pipelines in production environments * Strong understanding of data engineering principles and data lifecycle ...

Data Engineer

Bentonville, AR · On-site

$97K - $117K/yr

Required : • 3+ years (Intermediate) or 5+ years (Specialist) of data engineering experience • Hands-on experience with Apache Airflow for pipeline orchestration • Proficiency in Apache Spark ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/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 ...

Data Engineer

Atlanta, GA

$110K - $132K/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 ...

Data Engineer

Jersey City, NJ · On-site

$119K - $143K/yr

Design and maintain robust dbt models (staging, intermediate, marts) following analytics engineering best practices * Implement dbt tests, documentation, macros, and incremental models to ensure data ...

Data Engineer

Loudoun, VA · On-site

$129K - $155K/yr

Data Engineer Job Location: Reston, VA(100% Remote)(Non-Locals also will work) Position Type ... Ability to write intermediate to advanced SQL/Python for data ingestion and processing. * Support ...

Data Engineer

Alpharetta, GA · On-site

$110K - $132K/yr

Equifax is searching for an innovative Intermediate Data Engineer to join our Global Keying & Linking group. In this role, you will be a key contributor to a team dedicated to advancing data quality ...

Data Engineer

Dearborn, MI · Hybrid

$115K - $192K/yr

Intermediate Python Coding: Proficiency in writing clean, maintainable code for data manipulation ... Master's Degree in Computer Science, Data Engineering, or a related quantitative field. * 5+ years ...

GCP Data Engineer

Bentonville, AR · On-site

$100K - $120K/yr

... Intermediate) or 5+ years (Specialist) of data engineering experience • Hands-on experience with Apache Airflow for pipeline orchestration • Proficiency in Apache Spark for large-scale data ...

GCP Data Engineer

Bentonville, AR · On-site

$100K - $120K/yr

... Intermediate) or 5+ years (Specialist) of data engineering experience • Hands-on experience with Apache Airflow for pipeline orchestration • Proficiency in Apache Spark for large-scale data ...

Data Engineer

Juno Beach, FL · On-site

$111K - $134K/yr

As a Data Engineer, you will apply basic to intermediate machine learning techniques where applicable * Experiment with and support LLM-based solutions (prompting, embeddings, APIs) as needed

Data Engineer

Lewisville, TX · On-site

$75K - $93K/yr

This role is ideal for a beginner-to-intermediate professional who is excited to help build ... Experience: 1-3 years in data engineering, analytics engineering, or a data-heavy technical role.

Data Engineer

Chantilly, VA

$118K - $142K/yr

Data Engineer Location: Chantilly, VA Work Schedule: Full-Time, Onsite Clearance Required: Active ... Design and optimize data storage solutions utilizing AWS S3 for raw, intermediate, and production ...

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Data Engineer Intermediate information

See salary details

$44.5K

$129.7K

$177.5K

How much do data engineer intermediate jobs pay per year?

As of Jul 17, 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 is an intermediate data engineer?

An intermediate data engineer is a professional who designs, builds, and maintains data pipelines and infrastructure, typically with several years of experience. They are proficient in tools like SQL, Python, and cloud platforms, and often work on optimizing data workflows and ensuring data quality. This role requires a solid understanding of data modeling, ETL processes, and basic knowledge of distributed systems.

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 engineer makes 500,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such roles often require strong programming, data architecture, and leadership capabilities, along with relevant certifications and a track record of managing complex data systems.

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 engineers make 300,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn salaries of $300,000 or more annually. High compensation is often associated with working in large organizations, possessing specialized certifications, and leading complex data projects.

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 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.

Can I get a data engineer job with no experience?

Entry-level data engineer positions typically require some knowledge of programming, databases, and data processing tools like SQL, Python, or cloud platforms. While prior experience is often preferred, candidates with relevant internships, certifications, or strong technical skills can sometimes qualify for junior roles or apprenticeships in data engineering.
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

$116K - $139K/yr

Other

Medical, Retirement

Re-posted 12 days ago


Job description

Index Analytics, LLC, is a rapidly growing Baltimore-based small business providing health related consulting services to the federal government. At the center of our company culture is a commitment to instilling a dynamic and employee-friendly place to work. We place a priority on promoting a supportive and collegial team environment and enhancing staff’s experience through career development and educational opportunities. 

Job Overview 

As a Data Engineer in this role, you will apply advanced data engineering principles to create reusable workflows that cover ingestion, quality assurance, transformation, and optimization of data. You will be responsible for building scalable pipelines using ETL tools, ensuring that data is efficiently extracted, transformed, and loaded into target systems. Your work will involve deploying robust data solutions into production environments and migrating information from legacy data warehouses by leveraging modern cloud architecture, particularly within Microsoft Azure SQL and Snowflake environments. Automating the flow of data for seamless consumption will be a key aspect of your daily responsibilities.

You will also play a pivotal role in establishing business processes that support strong data governance practices. This includes designing and advising on comprehensive data quality rules and setting up effective data compliance policies to ensure organizational standards are met. Exposure to ETL pipeline development, cloud-based data migration, and the implementation of data governance frameworks will be highly beneficial. Experience with optimizing data workflows, deploying solutions in cloud environments, and automating data processes will help you excel in this position. 

Responsibilities 

This role is centered on Snowflake as the primary data platform. Candidates are expected to demonstrate deep experience designing, developing, and optimizing enterprise-scale data solutions within Snowflake environments.

  • Apply data engineering principles to develop reusable workflows for data ingestion, quality, transformation, and optimization
  • Set up and maintain effective data compliance policies
  • Build scalable data pipelines using ETL tools and processes
  • Deploy data solutions to production environments
  • Migrate data from legacy data warehouses leveraging cloud architecture principles
  • Automate the flow of data for efficient consumption
  • Build and implement business processes that enable data governance
  • Design and advise on data quality rules
  • U.S. citizen or otherwise authorized to work in the United States and able to demonstrate physical residency in the U.S. for at least three (3) of the past five (5) years. Must be able to obtain a U.S. Federal government client badge and pass a Public Trust clearance.
  • Bachelor’s Degree or equivalent OR 4 years’ relevant experience in lieu of degree
  • 7 additional years of relevant experience
  • Ability to gain and hold a Public Trust clearance

Technical Requirements:

  • Hands-on experience with:
    • Microsoft SQL Server (Intermediate proficiency)
    • Snowflake platform (Intermediate proficiency)
    • ETL pipeline design and development (Intermediate proficiency)
    • Microsoft Azure SQL (Intermediate proficiency)
  • Experience building and deploying data pipelines in production environments
  • Strong understanding of data engineering principles and data lifecycle management

Professional Requirements:

  • Ability to work independently and collaboratively in cross-functional teams
  • Strong organizational, time management, and multitasking skills
  • High attention to detail and commitment to data quality and accuracy

Preferred Qualifications

  • Experience with modern cloud data architecture and platforms
  • Proficiency with ETL tools such as Informatica, Talend, Azure Data Factory, or dbt
  • Experience with cloud-based governance frameworks and implementation
  • Experience with automation or scripting (E.g., Python, SQL, CI/CD pipelines)

Attention Candidates

We're dedicated to ensuring a safe and transparent recruitment process for all candidates and have implemented robust measures to protect your personal information. Please be aware that all employment-related communications will originate from a secure portal (NAME@msg.paycomonline.com) or a corporate email address (NAME@index-analytics.com). If you have any concerns, please don't hesitate to reach out to us at recruiting@index-analytics.com.

If you are selected for an interview, please be advised that Index Analytics LLC reserves the right to prohibit the use of artificial intelligence (AI) tools, including but not limited to AI-generated responses, real-time transcription, or automated assistance during the interview process. We value authentic interactions and the opportunity to engage directly with candidates. Any unauthorized use of AI may result in disqualification from consideration.

The salary range provided represents the estimated compensation for new hires in this position, applicable across all locations. Actual offers may vary based on factors such as the candidate's skills, qualifications, experience, and market conditions. Index complements its base salary offering with a competitive package that includes health and retirement benefits, discretionary bonuses, and reimbursement for professional development opportunities.

Index Analytics provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.