ZipRecruiter

Log In

2

No Experience Data Engineer Jobs in Springfield, IL

MSR Technology Group

ETL Data Engineer

Springfield, IL · Remote

$113.50K - $136.30K/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 ...

DataAnnotation

Data Science Consultant

Springfield, IL · On-site +1

$40/hr

We are looking for experienced quantitative professionals to help advance AI development. AI models ... Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g ...

State of Illinois

Permit Engineer

Springfield, IL

$5.43K - $8.82K/mo

No matter what state career you're looking for, we offer jobs that fit your life and your schedule ... Collects data for assigned projects, including river stages, precipitation, high water information ...

State of Illinois

Permit Engineer

Springfield, IL

$5.43K - $8.82K/mo

No matter what state career you're looking for, we offer jobs that fit your life and your schedule ... Collects data for assigned projects, including river stages, precipitation, high water information ...

State of Illinois

Permit Engineer

Springfield, IL · On-site

$5.43K/mo

No matter what state career you're looking for, we offer jobs that fit your life and your schedule ... Collects data for assigned projects, including river stages, precipitation, high water information ...

next page

Showing results 1-20

People also search for

All 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 May 29, 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 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 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.

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.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining data infrastructure, and their skills in managing complex systems and understanding business needs remain critical even as AI tools assist with routine tasks.

What engineering jobs pay $500,000?

High-level engineering roles such as senior data engineers, software engineers, and engineering managers can reach or exceed $500,000 annually, especially with experience, bonuses, and stock options. These positions often require advanced skills, certifications, and leadership responsibilities in technology companies or financial firms.

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 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

$113.50K - $136.30K/yr

Full-time

Posted 6 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