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Data Processing Jobs in Indiana (NOW HIRING)

Be up to date with data processing technology / platforms such as Spark (Databricks) * Experienced in Azure DevOps * Desirable * Experience of working in tightly regulated industry is desirable

Sr. Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

... processes.**Key Responsibilities** · Design, build, and maintain scalable data pipelines integrating POS, eCommerce, third-party, and enterprise data sources · Lead cross-platform data integration ...

Sr. Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

... processes. Key Responsibilities • Design, build, and maintain scalable data pipelines integrating POS, eCommerce, third-party, and enterprise data sources • Lead cross-platform data integration ...

Automate data processing workflows using Python to support scalable, repeatable analytics ... operations. * Query and integrate data from external sources, including APIs, web services, and RSS ...

Automate data processing workflows using Python to support scalable, repeatable analytics ... operations. * Query and integrate data from external sources, including APIs, web services, and RSS ...

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process. Data Analyst Full Time Odon, IN, US 1 ...

Data Modeler

Indianapolis, IN · Remote

$52.25 - $67.75/hr

Drive automation and modernization of data infrastructure and integration processes to support agile analytics initiatives. Cummins is an equal opportunity employer. Our policy is to provide equal ...

Data Modeler

Indianapolis, IN · Remote

$52.25 - $67.75/hr

Drive automation and modernization of data infrastructure and integration processes to support agile analytics initiatives. Cummins is an equal opportunity employer. Our policy is to provide equal ...

Data Engineer

Indianapolis, IN · On-site

$102K - $123K/yr

Develop secure processes for exchanging data through APIs, flat files, SFTP, EDI transactions, healthcare interoperability standards, and other integration mechanisms as required. * Support real-time ...

Data Modeler

Indianapolis, IN · Remote

$52.25 - $67.75/hr

Drive automation and modernization of data infrastructure and integration processes to support agile analytics initiatives. Cummins is an equal opportunity employer. Our policy is to provide equal ...

Data Modeler

Indianapolis, IN · On-site +1

$123K - $150K/yr

Drive automation and modernization of data infrastructure and integration processes to support agile analytics initiatives. Responsibilities To be successful in this role you will need the following:

Process and organize geospatial datasets from multiple sensors including LiDAR, GPR, GNSS, and ... Ensure data is properly archived and backed up according to company protocols. * Communicate ...

Data Engineer

Indianapolis, IN · On-site +1

$102K - $123K/yr

Develop secure processes for exchanging data through APIs, flat files, SFTP, EDI transactions, healthcare interoperability standards, and other integration mechanisms as required. * Support real-time ...

Process and organize geospatial datasets from multiple sensors including LiDAR, GPR, GNSS, and ... Ensure data is properly archived and backed up according to company protocols. * Communicate ...

Showing results 21-40

Data Processing information

See Indiana salary details

$11

$19

$33

How much do data processing jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for data processing in Indiana is $19.28, according to ZipRecruiter salary data. Most workers in this role earn between $15.34 and $21.25 per hour, depending on experience, location, and employer.

What is data processing?

A Data Processing job involves collecting, organizing, and managing data to ensure accuracy and accessibility. Professionals in this role use software tools to input, clean, analyze, and process data for businesses or organizations. They may also generate reports and automate workflows to streamline data handling. Strong attention to detail and proficiency in data management tools are essential for success in this field.

What are the typical daily responsibilities of someone working in data processing?

A typical day for a Data Processing professional involves entering, validating, and updating records in databases or spreadsheets to ensure data integrity. You may also be responsible for generating reports, cleaning large data sets, and identifying discrepancies or errors for correction. Collaboration with team members or departments is common to clarify data requirements and resolve issues. Staying organized and attentive to detail is essential because the quality of processed data can impact decision-making across the organization.

What are the key skills and qualifications needed to thrive in data processing, and why are they important?

To thrive in Data Processing, you need strong analytical abilities, attention to detail, and proficiency with spreadsheets and database management, often supported by an associate's degree or relevant experience. Familiarity with tools like Microsoft Excel, SQL, or data entry software, as well as certifications such as Certified Data Processor (CDP), are frequently expected. Strong organizational skills, time management, and the ability to troubleshoot problems efficiently are valued soft skills. These competencies are crucial for ensuring data accuracy, meeting deadlines, and supporting smooth information operations within an organization.

What do you do as a data processing?

A data processing professional collects, organizes, and analyzes data to ensure accuracy and usability. They use tools like spreadsheets, databases, and data management software to clean, transform, and prepare data for reporting or decision-making. Attention to detail and knowledge of data handling techniques are essential in this role.

What is a data processing job role?

A data processing job involves collecting, organizing, and converting raw data into a usable format for analysis or reporting. It often requires skills in data management tools, attention to detail, and knowledge of data formats and software such as Excel, SQL, or specialized processing programs.

What are the most commonly searched types of Data Processing jobs in Indiana?

The most popular types of Data Processing jobs in Indiana are:

What job categories do people searching Data Processing jobs in Indiana look for?

The top searched job categories for Data Processing jobs in Indiana are:

Infographic showing various Data Processing job openings in Indiana as of September 2026, with employment types broken down into 1% Internship, 2% As Needed, 82% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $40,111 per year, or $19.3 per hour.

Azure Data Engineer

Indianapolis, IN • On-site

Full-time

Posted 4 days ago


Quest Global rating

7.8

Company rating: 7.8 out of 10

Based on 11 frontline employees who took The Breakroom Quiz


Job description

Job Requirements

A data engineer works on implementing complex data projects with a focus on collecting, parsing, managing, analysing and visualising large sets of data to turn information into value using multiple platforms. 

You will work with business analysts, architects and data scientists to understand customer business problems and needs, secure the data supply chain, implement analysis solutions and visualise outcomes that support improved decision making for a customer. 

Key Accountabilities 

  1. Working with colleagues to understand and implement data product requirements 
  2. Delivering the data supply chain, understanding how data is ingested from different sources and combined / transformed into a single data set 
  3. Understanding how to analyse, cleanse, join and transform data 
  4. Implementing designed / specified solutions into the chosen platform with due consideration for Data Ops principles 
  5. Working with colleagues to ensure that the cloud infrastructure available is capable of meeting the solution requirements 
  6. Planning, designing and conducting tests of the implementations, correcting errors and re-testing to achieve an acceptable result 
  7. Appreciate how to manage the data including security, archiving, structure and storage 
  8. Support solution architect in creating architecture deliverables such as data architecture, data processing architecture, data testing strategy 

Key Experience and Qualifications 

  1. Degree level education in Mathematics, Scientific, Computing or Engineering discipline or equivalent experience 
  2. Mandatory 
  3. 6+ years of experience of Data Engineering roles including 2+ years in leading end-to-end design and implementation of data solutions for large scale use cases 
  4. Experience in designing solutions using databases and data storage technology using Azure data management components - Azure SQL, ADLS, Cosmos 
  5. Experience building, optimizing and automating data pipelines, architectures and data sets using MS Azure data management and processing components through IaaS/PaaS/SaaS implementation models implemented through custom solutions 
  6. Proficiency in Python using different modules used for data munging 
  7. Be up to date with data processing technology / platforms such as Spark (Databricks) 
  8. Experienced in Azure DevOps 
  9. Desirable 
  • Experience of working in tightly regulated industry is desirable 
  • Experience with ETL and/or data integration tool such as Informatica, Datastage, SSIS is highly desirable 
  • Good understanding of Azure infrastructure components and their fit in different types of data solutions 

Work Experience

A data engineer works on implementing complex data projects with a focus on collecting, parsing, managing, analysing and visualising large sets of data to turn information into value using multiple platforms. 

You will work with business analysts, architects and data scientists to understand customer business problems and needs, secure the data supply chain, implement analysis solutions and visualise outcomes that support improved decision making for a customer. 

Key Accountabilities 

  1. Working with colleagues to understand and implement data product requirements 
  2. Delivering the data supply chain, understanding how data is ingested from different sources and combined / transformed into a single data set 
  3. Understanding how to analyse, cleanse, join and transform data 
  4. Implementing designed / specified solutions into the chosen platform with due consideration for Data Ops principles 
  5. Working with colleagues to ensure that the cloud infrastructure available is capable of meeting the solution requirements 
  6. Planning, designing and conducting tests of the implementations, correcting errors and re-testing to achieve an acceptable result 
  7. Appreciate how to manage the data including security, archiving, structure and storage 
  8. Support solution architect in creating architecture deliverables such as data architecture, data processing architecture, data testing strategy 

Key Experience and Qualifications 

  1. Degree level education in Mathematics, Scientific, Computing or Engineering discipline or equivalent experience 
  2. Mandatory 
  3. 6+ years of experience of Data Engineering roles including 2+ years in leading end-to-end design and implementation of data solutions for large scale use cases 
  4. Experience in designing solutions using databases and data storage technology using Azure data management components - Azure SQL, ADLS, Cosmos 
  5. Experience building, optimizing and automating data pipelines, architectures and data sets using MS Azure data management and processing components through IaaS/PaaS/SaaS implementation models implemented through custom solutions 
  6. Proficiency in Python using different modules used for data munging 
  7. Be up to date with data processing technology / platforms such as Spark (Databricks) 
  8. Experienced in Azure DevOps 
  9. Desirable 
  • Experience of working in tightly regulated industry is desirable 
  • Experience with ETL and/or data integration tool such as Informatica, Datastage, SSIS is highly desirable 
  • Good understanding of Azure infrastructure components and their fit in different types of data solutions 


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