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Remote Data Conversion Developer Jobs in Illinois

MSR Technology Group

ETL Data Engineer

Springfield, IL · Remote

$113.50K - $136.30K/yr

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 ...

PAR Technology

Sr. Data Engineer

Chicago, IL · On-site +1

$130K - $144K/yr

Remote, United States Reports To: Engineering Manager What We're Looking For: Requirements: * Experience : 5+ years of experience in data engineering or related roles * Project Management

Apex Systems

Cloud Data Engineer

Oak Brook, IL · Remote

$115.70K - $138.90K/yr

Oak Brook, Illinois (Remote) Employment Type: Contract to Perm Role Overview This position is for ... Experience with DevOps tool chains and processes. Preferred Qualifications * Healthcare industry ...

SECURE RPO LLC

Data Scientist

Chicago, IL · On-site +1

... remote monitoring and data analytics methods to continuously improve EHC efficiency and effectiveness. Qualifications: Basic: * Bachelor's or Master's degree in Computer Science, Engineering ...

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Remote Data Conversion Developer information

What are the key skills and qualifications needed to thrive as a Remote Data Conversion Developer, and why are they important?

To thrive as a Remote Data Conversion Developer, you need strong programming skills (often in SQL, Python, or ETL tools), data mapping expertise, and an understanding of database structures, typically backed by a degree in computer science or related experience. Familiarity with data conversion platforms such as Informatica, Talend, or SSIS, and certifications in relevant tools or cloud services, are commonly required. Excellent problem-solving, attention to detail, and effective communication are crucial soft skills for collaborating remotely and managing complex data processes. These skills ensure accurate, efficient data transformations and seamless integration across diverse systems in a distributed work environment.

What are some common challenges faced by Remote Data Conversion Developers when working with legacy data systems?

Remote Data Conversion Developers often encounter challenges such as inconsistent data formats, incomplete or corrupted datasets, and undocumented legacy systems. Successfully converting and migrating data requires problem-solving skills to map and validate data accurately, as well as strong communication with business analysts and system owners to clarify requirements and resolve ambiguities. Additionally, thorough testing and quality assurance are essential to ensure data integrity throughout the conversion process.

What is a Remote Data Conversion Developer?

A Remote Data Conversion Developer is a professional who specializes in transforming data from one format or system to another, often working from a remote location. Their main responsibilities include analyzing existing data structures, designing conversion processes, writing scripts or software to automate data migration, and ensuring data integrity during the conversion. They typically work with databases, data warehouses, or legacy systems to facilitate seamless data transitions during system upgrades or platform changes. Strong skills in programming, data analysis, and problem-solving are essential for this role.

What is the difference between Remote Data Conversion Developer vs Data Analyst?

AspectRemote Data Conversion DeveloperData Analyst
Required CredentialsTypically requires programming skills, data conversion tools, and sometimes certifications in data managementRequires analytical skills, proficiency in data visualization, and often a degree in statistics or related fields
Work EnvironmentPrimarily technical, focused on data transformation, ETL processes, and scriptingAnalytical, focused on interpreting data, creating reports, and providing insights
Employer & Industry UsageUsed in IT, data management, and software development sectorsCommon in finance, marketing, healthcare, and business intelligence sectors

The main difference is that Remote Data Conversion Developers focus on transforming and converting data using technical skills, while Data Analysts interpret and analyze data to support decision-making. Both roles may work remotely and require familiarity with data tools, but their core responsibilities differ significantly.

What are the most commonly searched types of Data Conversion Developer jobs in Illinois? The most popular types of Data Conversion Developer jobs in Illinois are:
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What job categories do people searching Remote Data Conversion Developer jobs in Illinois look for? The top searched job categories for Remote Data Conversion Developer jobs in Illinois are:
What cities in Illinois are hiring for Remote Data Conversion Developer jobs? Cities in Illinois with the most Remote Data Conversion Developer job openings:
Remote Data Conversion Developer 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