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No Experience Data Engineer Jobs in Springfield, IL

MSR Technology Group

ETL Data Engineer

Springfield, IL · Remote

$113K - $136K/yr

The right candidate will have a strong background in Python-based data engineering, Azure data services, and experience modernizing legacy ETL environments. Core Responsibilities ETL Modernization ...

BJC HealthCare

Biomed Tech I

Springfield, IL · On-site

$25 - $33.25/hr

No Experience Supervisor Experience * No Experience Preferred Requirements Education * Associate's Degree - Engineering/Biomed Eng/related Experience * Supervisor Experience * Licenses ...

U.S. Navy

Civil Engineer

Springfield, IL · On-site

$2.9K - $5.8K/mo

There are no uniforms, no drilling, and no service obligation until after you graduate. Simply work ... hands-on experience and advanced training in civil engineering areas including architecture ...

Hilti

Field Engineer

New City, IL

Provide field testing to determine appropriate capabilities in situations not covered by test data ... Knowledge of construction methods and practices preferred * 2 years minimum experience in ...

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All JobsData Engineer JobsNo Experience Data Engineer JobsNo Experience Data Engineer Jobs in Springfield, IL

No Experience Data Engineer information

See Springfield, IL salary details

$44.1K

$128.6K

$175.9K

How much do no experience data engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for no experience data engineer in Springfield, IL is $128,563.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

What is the difference between No Experience Data Engineer vs Data Engineer?

AspectNo Experience Data EngineerData Engineer
Required CredentialsBasic understanding of data concepts, entry-level certificationsDegree in Computer Science or related field, advanced certifications often preferred
Work EnvironmentInternships, entry-level roles, training programsFull-time professional roles in tech or data teams
Employer & Industry UsageStartups, companies hiring entry-level data rolesTech companies, finance, healthcare, and large enterprises
Search & Comparison IntentYesYes

The main difference between a No Experience Data Engineer and a Data Engineer lies in experience and qualifications. The No Experience Data Engineer is typically an entry-level role suited for those just starting, often requiring basic data knowledge and certifications. In contrast, a Data Engineer usually has relevant experience, a degree, and advanced skills, working in more complex environments. Both roles are essential in data-driven organizations, but they differ significantly in responsibilities and expectations.

What are 'No Experience Data Engineers'?

No Experience Data Engineers are individuals who are entering the field of data engineering without prior professional experience in the role. They may have relevant educational backgrounds or have completed certifications and personal projects, but are seeking entry-level positions to gain practical, on-the-job experience. These roles typically involve learning to build and maintain data pipelines, manage databases, and work with big data tools under the guidance of more experienced engineers. Employers look for foundational skills in programming, SQL, and an understanding of data systems, even if the candidate has not previously worked as a data engineer.

Can I make 200k as a data engineer?

Achieving a salary of 200k as a data engineer is possible, especially with significant experience, advanced skills in tools like Spark or cloud platforms, and working in high-cost-of-living areas or senior roles. Entry-level data engineers typically earn lower salaries, but with experience, certifications, and specialization, higher compensation is attainable.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data processing and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining data systems, and their skills in programming, database management, and system architecture remain in high demand. AI tools can augment their work but do not eliminate the need for human expertise in complex data environments.

What engineers make $500,000?

Highly experienced data engineers with specialized skills in big data, cloud platforms, and advanced analytics can earn $500,000 or more annually, especially in senior or leadership roles at large companies. Achieving this level typically requires extensive experience, advanced certifications, and a strong track record of managing complex data infrastructure.

What are some effective ways for entry-level Data Engineers to quickly gain practical experience and contribute to their team?

As an entry-level Data Engineer, you can quickly gain practical experience by volunteering for small-scale data projects, assisting with data pipeline maintenance, and exploring internal documentation. Collaborating closely with senior engineers and asking for feedback accelerates learning and helps you understand best practices. Participating in code reviews and pair programming sessions also enhances your technical and teamwork skills, making it easier to contribute meaningfully to your team’s objectives.

Can I get a data engineer job with no experience?

Entry-level data engineering roles often require some knowledge of programming, databases, and data processing tools like SQL, Python, or cloud platforms. While prior experience is not always mandatory, demonstrating relevant skills through projects, certifications, or coursework can improve chances of securing such positions.

What are the key skills and qualifications needed to thrive as a No Experience Data Engineer, and why are they important?

To thrive as a No Experience Data Engineer, you need a strong understanding of data structures, SQL, and basic programming languages such as Python or Java, often backed by a degree in computer science or a related field. Familiarity with tools like SQL databases, ETL pipelines, and cloud platforms (e.g., AWS, Google Cloud) is highly beneficial, and obtaining entry-level certifications can be helpful. Strong problem-solving abilities, attention to detail, and a willingness to learn are critical soft skills for those starting out in this field. These skills and qualities enable newcomers to efficiently manage, process, and analyze data, laying a solid foundation for growth in data engineering roles.
What are the most commonly searched types of Data Engineer jobs in Springfield, IL? The most popular types of Data Engineer jobs in Springfield, IL are:
What are popular job titles related to No Experience Data Engineer jobs in Springfield, IL? For No Experience Data Engineer jobs in Springfield, IL, the most frequently searched job titles are:
What job categories do people searching No Experience Data Engineer jobs in Springfield, IL look for? The top searched job categories for No Experience Data Engineer jobs in Springfield, IL are:
What cities near Springfield, IL are hiring for No Experience Data Engineer jobs? Cities near Springfield, IL with the most No Experience Data Engineer job openings:
No Experience Data Engineer jobs near you

ETL Data Engineer

MSR Technology Group

Springfield, IL • Remote

$113K - $136K/yr

Full-time

Posted 22 days ago

Job description

Senior Data Engineer – Azure / Python ETL Modernization
Remote (U.S.) with Minimal travel (2–3x per year)
Overview
We’re hiring a Senior Data Engineer to lead enterprise ETL modernization initiatives, transitioning legacy data pipelines (e.g., Informatica, on-prem data warehouses) into modern Azure-based, Python-driven data platforms.
This is a hands-on engineering role focused on building scalable data pipelines, refactoring legacy logic into Python/PySpark, and delivering production-grade data solutions that support analytics, reporting, and downstream data use cases.
The right candidate will have a strong background in Python-based data engineering, Azure data services, and experience modernizing legacy ETL environments.
Core Responsibilities
ETL Modernization (Primary Focus)
  • Refactor and migrate legacy ETL pipelines (e.g., Informatica) into Python/PySpark-based pipelines
  • Translate business logic into scalable, code-driven transformations (not tool-based ETL)
  • Support large-scale migration from on-prem data warehouses to Azure
Data Pipeline Engineering
  • Build and maintain pipelines using Azure Data Factory, Synapse Pipelines, and/or Databricks
  • Develop reusable, parameter-driven frameworks for ingestion and transformation
  • Implement ELT patterns leveraging SQL pushdown and distributed processing
Python & Spark Development
  • Develop and optimize PySpark jobs for large-scale data processing
  • Write clean, testable Python code for transformation, orchestration, and data quality
  • Integrate with APIs and external data sources
Data Architecture & Modeling
  • Implement lakehouse architecture (ADLS Gen2, Delta Lake, Parquet)
  • Design dimensional models (star/snowflake) for analytics use
  • Handle SCD (Type 1/2), CDC, and complex transformation logic
Platform & DevOps
  • Build CI/CD pipelines using Azure DevOps (YAML, Terraform/Bicep)
  • Implement monitoring, logging, and alerting (Azure Monitor, Log Analytics)
  • Ensure security and access controls (RBAC, Key Vault, networking)
Required Skills
  • Strong hands-on experience with Python for data engineering (non-negotiable)
  • Solid experience with PySpark / Spark-based processing frameworks
  • Experience with Azure Data Factory, Synapse, or Databricks
  • Advanced SQL (complex transformations, optimization, performance tuning)
  • Experience working with modern data lakes (ADLS Gen2, Delta Lake)
  • Experience with ETL modernization or legacy system migration
  • Familiarity with CI/CD and DevOps practices in data engineering
Preferred Experience
  • Background migrating Informatica or similar ETL tools into Python-based frameworks
  • Experience with large enterprise data warehouse environments (Teradata, SQL Server, Oracle)
  • Exposure to regulated environments (healthcare, financial, etc.)
  • Snowflake experience is a plus
Why This Role Is Different
  • Focus on real modernization work, not legacy ETL maintenance
  • Heavy emphasis on Python-first data engineering
  • Opportunity to influence architecture and engineering standards
  • Long-term, high-impact enterprise data platform