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Remote Data Engineering Jobs in Plainfield, IL (NOW HIRING)

Kemper

Data Quality Engineer

Chicago, IL · Remote

$118K - $141K/yr

... Remote-OH, Remote-PA, Remote-RI, Remote-VA Details Kemper is one of the nation's leading ... As a senior member of the data engineering team, you will be responsible for developing scalable ...

Kemper

Data Quality Engineer

Downers Grove, IL · Remote

$114K - $137K/yr

... Remote-OH, Remote-PA, Remote-RI, Remote-VA Details Kemper is one of the nation's leading ... As a senior member of the data engineering team, you will be responsible for developing scalable ...

Kemper

Principal Data Engineer

Downers Grove, IL · On-site +1

Location(s) Chicago, Illinois, Downers Grove, Illinois, Remote-AL, Remote-CT, Remote-FL, Remote-GA ... This role provides hands-on technical leadership across data engineering initiatives, cloud ...

Kemper

Principal Data Engineer

Chicago, IL · On-site +1

Location(s) Chicago, Illinois, Downers Grove, Illinois, Remote-AL, Remote-CT, Remote-FL, Remote-GA ... This role provides hands-on technical leadership across data engineering initiatives, cloud ...

Collectiv

Data Engineer (Azure, Fabric, Databricks)

Chicago, IL · On-site +1

$118K - $141K/yr

Ensure data quality, reliability, and usability across the analytics platform Engineering Best ... At Collectiv, your career thrives with a perfect blend of remote flexibility, growth potential, and ...

Kemper

Senior Data Engineer

Downers Grove, IL · Remote

$105K - $143K/yr

... PA, Remote-RI, Remote-VA, St. Louis, Missouri Details Kemper is one of the nation's leading ... Mentor engineering team members,facilitatecode reviews, and promote continuous learning and ...

NinjaHoldings

Data Engineer

Chicago, IL · On-site +1

$100K - $145K/yr

With offices in Chicago, Miami, and around the world through the power of remote work, we are a ... Supervise junior members of the data engineering team. Guiding, planning, and reviewing the team ...

Kemper

Senior Data Engineer

Chicago, IL · Remote

$109K - $148K/yr

... PA, Remote-RI, Remote-VA, St. Louis, Missouri Details Kemper is one of the nation's leading ... Mentor engineering team members,facilitatecode reviews, and promote continuous learning and ...

NinjaHoldings

Data Engineer

Chicago, IL · On-site +1

$100K - $145K/yr

With offices in Chicago, Miami, and around the world through the power of remote work, we are a ... Supervise junior members of the data engineering team. Guiding, planning, and reviewing the team ...

RxSaveCard Inc

Data Engineer (Remote)

Chicago, IL · Remote

$117K - $140K/yr

Key Responsibilities Data Engineering * Design, build, and maintain scalable data pipelines for ... Remote or hybrid Chicago work flexibility * Collaborative and dynamic team environment * The chance ...

VeeRteq Solutions Inc.

Data Modeler

Chicago, IL · Remote

$56 - $72.75/hr

Remote (Prefer PST, 2nd Preference CST) USA Experience: Minimum 10+ years As a Senior Data Modeler ... Collaborate with ETL and Data Engineering teams on data ingestion, orchestration, and ...

New

1 point system

Data Engineer

Chicago, IL · Remote

$117K - $140K/yr

10+ years of IT experience, including deep expertise in data engineering & ETL. 4-6+ years of recent hands-on experience in designing, building, and scaling data pipelines. Strong hands-on experience ...

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All JobsData Engineering JobsRemote Data Engineering JobsRemote Data Engineering Jobs in Plainfield, IL

Remote Data Engineering information

See Plainfield, IL salary details

$43.4K

$126.4K

$173K

How much do remote data engineering jobs pay per year?

As of Jul 27, 2026, the average yearly pay for remote data engineering in Plainfield, IL is $126,435.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,600.00 and $134,000.00 per year, depending on experience, location, and employer.

Can I work remotely as a data engineer?

Yes, remote data engineering roles are common, allowing professionals to work from various locations. These jobs often require skills in cloud platforms, programming, and data pipeline tools, and may involve collaboration through online communication tools.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote data engineers often work with distributed teams, which requires strong communication and organization skills. They collaborate using tools like Slack, Zoom, and project management platforms to stay aligned on data pipeline development, troubleshooting, and deployment. Regular stand-ups, asynchronous documentation, and clear communication of progress are essential for ensuring everyone is on the same page, regardless of location. Flexibility in working hours and proactive scheduling of meetings help facilitate effective collaboration and project delivery.

What is remote data engineering?

Remote data engineering involves designing, building, and maintaining data systems and pipelines while working from a location outside of a traditional office. Remote data engineers use tools to collect, process, and store large sets of data, making it accessible for analysis and business decision-making. They collaborate with teams virtually, often using cloud-based technologies, to ensure that data infrastructure is reliable, scalable, and secure. This role requires strong technical skills in programming, databases, and data architecture, as well as the ability to communicate effectively in a distributed work environment.

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

To thrive as a Remote Data Engineer, you need strong programming skills (such as Python, Java, or Scala), experience with data modeling, ETL processes, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Proficiency with big data tools like Apache Spark, Hadoop, cloud platforms (AWS, Azure, GCP), and certifications in these technologies is highly valued. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These competencies ensure effective data pipeline development, reliable data management, and seamless teamwork across distributed environments.

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 compensation often includes bonuses, stock options, and other incentives.

How to make $1000 a week remote?

Remote data engineers can earn $1000 or more per week by working on high-demand projects, leveraging specialized skills in data pipelines, cloud platforms, and programming languages like Python or SQL. Building a strong portfolio, obtaining relevant certifications, and working with multiple clients or on freelance platforms can help increase weekly income. Consistent remote work and advanced expertise are key to reaching this earning level.

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 complex data systems, and their expertise in tools like SQL, Python, and cloud platforms remains critical for managing data workflows effectively.

What is the difference between Remote Data Engineering vs Remote Data Analyst?

AspectRemote Data EngineeringRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with SQL, Python, cloud platformsBachelor's in Statistics, Data Science, or related; proficiency in Excel, SQL, visualization tools
Work EnvironmentBuilds data pipelines, manages databases, works with cloud infrastructureAnalyzes data sets, creates reports, visualizes data insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, finance, retail, consulting

Remote Data Engineering focuses on designing and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require strong analytical skills but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Engineering jobs in Plainfield, IL? The most popular types of Data Engineering jobs in Plainfield, IL are:
What are popular job titles related to Remote Data Engineering jobs in Plainfield, IL? For Remote Data Engineering jobs in Plainfield, IL, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineering jobs in Plainfield, IL look for? The top searched job categories for Remote Data Engineering jobs in Plainfield, IL are:
What cities near Plainfield, IL are hiring for Remote Data Engineering jobs? Cities near Plainfield, IL with the most Remote Data Engineering job openings:
Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in Plainfield, IL as of July 2026, with employment types broken down into 70% Full Time, 10% Part Time, 5% Temporary, and 15% Contract. Highlights an 100% Remote job distribution, with an average salary of $126,435 per year, or $60.8 per hour.
Remote Data / Persistence Modernization Engineer

Remote Data / Persistence Modernization Engineer

3B Staffing LLC

West Chicago, IL • Remote

$117K - $140K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Title: Data / Persistence Modernization Engineer Primary Location: Primarily Remote, Candidates Ideally Reside in Chicagoland Area Position Type: Contract, 6 months with possible extension Overview Looking for a Data / Persistence Modernization Engineer to join our client's cloud modernization initiative. This senior-level consultant will assess stateful application services, data platforms, caching technologies, search solutions, analytics stores, and data-migration patterns associated with both recurring modernization efforts and newly acquired environments. The engineer will determine whether material data dependencies can be migrated directly, bridged temporarily, retained through a controlled exception, replaced with a target-platform service, or require application data-layer refactoring. This role combines architecture assessment, hands-on technical validation, migration planning, risk analysis, and engineering-effort estimation. What You Bring to the Role. (Ideal Experience)
  • Senior-level experience modernizing application data layers and distributed persistence architectures.
  • Deep experience with NoSQL and document-oriented platforms, including:
    • Amazon DynamoDB
    • Amazon DocumentDB
    • MongoDB and MongoDB Atlas
  • Working knowledge of:
    • PostgreSQL and PostgreSQL-based managed services
    • Amazon RDS
    • Google AlloyDB
    • Redis and Amazon ElastiCache
    • OpenSearch
    • Snowflake
    • Amazon Redshift
  • Strong understanding of data-access patterns, schema design, indexing, and partitioning strategies.
  • Experience evaluating consistency models, transaction semantics, and data-model coupling.
  • Knowledge of cache-versus-state classification and the operational implications of each.
  • Hands-on experience with:
    • Change Data Capture
    • Data backfills
    • Dual-write patterns
    • Shadow reads
    • Data reconciliation
    • Tenant isolation
    • Data cutover and rollback strategies
  • Ability to assess application changes required when a managed cloud service cannot be directly reproduced on the target platform.
  • Strong written communication skills with the ability to produce concise, actionable engineering assessments.
  • Experience estimating technical complexity, platform dependencies, migration risks, and future engineering effort.
What You'll Do. (Skills Used in this Position)
  • Assess recurring and acquisition-specific risks related to stateful application services and data platforms.
  • Analyze data models, schemas, indexes, partitions, access patterns, consistency requirements, and transaction behavior.
  • Evaluate dependencies involving databases, caches, search platforms, analytics stores, and managed cloud data services.
  • Determine whether each dependency is:
    • Portable to the target environment
    • Suitable for temporary bridging
    • Eligible for a controlled exception
    • A candidate for replacement
    • Likely to require application refactoring
  • Evaluate dual-running, reconciliation, backfill, and rollback options.
  • Identify required target-platform services, configurations, and technical prerequisites.
  • Perform bounded, non-production technical validation when additional evidence is needed.
  • Assess tenant isolation, data security, migration sequencing, and service availability risks.
  • Estimate the application, platform, data, testing, and operational effort associated with each migration path.
  • Produce concise Engineering Assessment Inputs documenting:
    • Data-model coupling
    • Access-pattern findings
    • Migration options
    • Platform dependencies
    • Cutover and rollback feasibility
    • Key risks and constraints
    • Likely future engineering effort
  • Partner with application teams, cloud platform teams, architects, security stakeholders, and data owners throughout the assessment process.

Apply