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Remote Cleaning Validation Engineer Jobs in Springfield, IL

MSR Technology Group

ETL Data Engineer

Springfield, IL · Remote

$113K - $136K/yr

Senior Data Engineer - Azure / Python ETL Modernization Remote (U.S.) with Minimal travel (2-3x per ... Write clean, testable Python code for transformation, orchestration, and data quality * Integrate ...

Hansoninc

Cultural Resource Specialist

Springfield, IL · On-site +1

$60K - $80K/yr

Coordinate with engineers, planners, environmental scientists, and project managers to support ... Valid driver's license and ability to travel for field assignments. Preferred Qualifications

All JobsCleaning Validation Engineer JobsRemote Cleaning Validation Engineer JobsRemote Cleaning Validation Engineer Jobs in Springfield, IL

Remote Cleaning Validation Engineer information

See Springfield, IL salary details

$22

$51

$77

How much do remote cleaning validation engineer jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for remote cleaning validation engineer in Springfield, IL is $51.53, according to ZipRecruiter salary data. Most workers in this role earn between $39.09 and $62.64 per hour, depending on experience, location, and employer.

What are Remote Cleaning Validation Engineers?

Remote Cleaning Validation Engineers are professionals who specialize in ensuring that cleaning processes in industries such as pharmaceuticals, biotechnology, and food production meet regulatory standards and are effective in removing contaminants. They perform validation activities, such as developing protocols, reviewing documentation, and analyzing data, all while working remotely using digital tools and communication platforms. Their main goal is to confirm that cleaning processes are reliable and reproducible, helping companies stay compliant with industry regulations. Their work often involves collaboration with on-site personnel and regulatory agencies. Remote Cleaning Validation Engineers play a crucial role in maintaining product safety and quality.

How does a Remote Cleaning Validation Engineer collaborate with on-site teams to ensure compliance and effective validation?

As a Remote Cleaning Validation Engineer, collaboration with on-site teams is typically achieved through regular virtual meetings, detailed documentation reviews, and the use of digital monitoring systems. You’ll often coordinate with production, quality assurance, and maintenance staff to gather process data, review cleaning procedures, and address compliance gaps. Effective communication is key, as you will provide guidance, troubleshoot remotely, and sometimes conduct virtual walkthroughs. Building strong working relationships and clear reporting structures helps ensure that all validation protocols are consistently met, even from a distance.

What is the difference between Remote Cleaning Validation Engineer vs Remote Quality Assurance Specialist?

AspectRemote Cleaning Validation EngineerRemote Quality Assurance Specialist
CertificationsGMP, validation, and industry-specific certificationsGMP, QA, and compliance certifications
Work EnvironmentPharmaceutical/biotech manufacturing, validation labsRegulatory agencies, manufacturing, quality departments
Employer & Industry UsagePharmaceutical, biotech, medical device companiesPharmaceutical, biotech, healthcare organizations

The Remote Cleaning Validation Engineer focuses on validating cleaning processes to ensure compliance with industry standards, while the Remote Quality Assurance Specialist oversees overall quality systems and compliance. Both roles require GMP knowledge and industry certifications, often working remotely within pharmaceutical or biotech sectors. The main difference lies in their specific responsibilities: validation versus quality assurance oversight.

What are the key skills and qualifications needed to thrive as a Remote Cleaning Validation Engineer, and why are they important?

To thrive as a Remote Cleaning Validation Engineer, you need a solid background in chemical engineering, biotechnology, or a related field, along with experience in cleaning validation processes and regulatory guidelines. Familiarity with validation protocols, data analysis tools, and documentation systems such as GMP software and LIMS is essential. Excellent attention to detail, problem-solving abilities, and strong communication skills are crucial for collaborating with cross-functional teams and ensuring compliance from a distance. These competencies ensure effective validation, regulatory compliance, and operational efficiency in remote or distributed manufacturing environments.
What are popular job titles related to Remote Cleaning Validation Engineer jobs in Springfield, IL? For Remote Cleaning Validation Engineer jobs in Springfield, IL, the most frequently searched job titles are:
What cities near Springfield, IL are hiring for Remote Cleaning Validation Engineer jobs? Cities near Springfield, IL with the most Remote Cleaning Validation Engineer job openings:
Remote Cleaning Validation Engineer jobs near you
Infographic showing various Remote Cleaning Validation Engineer job openings in Springfield, IL as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, 8% Part Time, 1% Temporary, and 3% Contract. Highlights an 42% Physical, 2% Hybrid, and 56% Remote job distribution, with an average salary of $107,191 per year, or $51.5 per hour.

ETL Data Engineer

MSR Technology Group

Springfield, IL • Remote

$113K - $136K/yr

Full-time

Posted 5 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