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Remote Data Engineering Jobs in Indiana (NOW HIRING)

Cummins

Data Engineer - Senior

Indianapolis, IN · On-site +1

$110K - $135K/yr

System Requirements Engineering - Uses appropriate methods and tools to translate stakeholder needs ... Data Extraction - Performs data extract-transform-load (ETL) activities from variety of sources and ...

Recruitment Room

$60 - $90/hr

Data Analysis / Analytics Expert Hourly Contract Remote Compensation: $60$90 per hour Overview We ... Collaborate remotely with engineers, researchers, and business teams. Ideal Qualifications * Degree ...

CSpring

Senior Data Analyst

Indianapolis, IN · On-site +1

$82K - $103K/yr

Our clients span the public and private sectors, and our work -- from data strategy and engineering ... with company's remote work policy. * Domestic travel required less than 2% of the time.

CSpring

Senior Data Analyst

Indianapolis, IN · On-site +1

$82K - $103K/yr

Our clients span the public and private sectors, and our work - from data strategy and engineering ... with company's remote work policy. * Domestic travel required less than 2% of the time.

Kobie Marketing

Director, Product

Indianapolis, IN · Remote

$222K - $233K/yr

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... You will work directly with Product, Data Engineering, Client Services, and Commercial teams to ...

Harris

Configure and manage map services and data publishing workflows to ensure timely and accurate data ... engineering role. * Strong proficiency in core GIS principles, including coordinate systems ...

Harris

Configure and manage map services and data publishing workflows to ensure timely and accurate data ... engineering role. * Strong proficiency in core GIS principles, including coordinate systems ...

Circle

Staff Software Engineer, Data Platform

Austin, IN · On-site +1

As a member of the Data Platform Engineering team, you own the core Data warehouse platform, data ... Excellent communication skills, with the ability to collaborate across multiple remote teams, share ...

Circle

Staff Software Engineer, Data Platform

Miami, IN · On-site +1

As a member of the Data Platform Engineering team, you own the core Data warehouse platform, data ... Excellent communication skills, with the ability to collaborate across multiple remote teams, share ...

Circle

Staff Software Engineer, Data Platform

Boston, IN · On-site +1

As a member of the Data Platform Engineering team, you own the core Data warehouse platform, data ... Excellent communication skills, with the ability to collaborate across multiple remote teams, share ...

Recruitment Room

$70 - $100/hr

Software Engineering / Development Expert Hourly Contract Remote Compensation: $70$100 per hour ... data structures, and system design. * Experience with agile methodologies and remote collaboration ...

JCD Staffing

UI/UX SME

Crane, IN · On-site +1

$185K/yr

... fully remote , and any required travel would be reimbursed by the government . The ideal candidate is a highly collaborative UX/UI professional who can work closely with data engineers, systems ...

Deckers

Chief Digital & Data Officer Location: United States (Remote) Interested applicants must reside in ... Collaborating with data architects, platform and DevOps engineering teams, product leaders, and ...

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All JobsData Engineering JobsRemote Data Engineering JobsRemote Data Engineering Jobs in Indiana

Remote Data Engineering information

See Indiana salary details

$42.3K

$123.4K

$168.9K

How much do remote data engineering jobs pay per year?

As of Jul 9, 2026, the average yearly pay for remote data engineering in Indiana is $123,433.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $130,800.00 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 Indiana? The most popular types of Data Engineering jobs in Indiana are:
What are popular job titles related to Remote Data Engineering jobs in Indiana? For Remote Data Engineering jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineering jobs in Indiana look for? The top searched job categories for Remote Data Engineering jobs in Indiana are:
What cities in Indiana are hiring for Remote Data Engineering jobs? Cities in Indiana with the most Remote Data Engineering job openings:
Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in Indiana as of July 2026, with employment types broken down into 72% Full Time, 17% Part Time, and 11% Contract. Highlights an 100% Remote job distribution, with an average salary of $123,433 per year, or $59.3 per hour.
Data Engineer - Senior

Data Engineer - Senior

Cummins

Indianapolis, IN • On-site, Remote

$110K - $135K/yr

Full-time

Posted 3 days ago

New

Cummins rating

8.1

Company rating: 8.1 out of 10

Based on 253 frontline employees who took The Breakroom Quiz

109th of 528 rated manufacturers

Job description


We are looking for a talented Data Engineer- Senior to join our team specializing in Systems/Information Technology for our Corporate organization in Indianapolis, IN.
In this role, you will make an impact in the following ways:
  • Enable reliable data flow at scale by designing and automating deployments for distributed systems that ingest and transform diverse data sources, ensuring consistent and seamless data availability across the organization.
  • Improve data trust and decision-making by building robust monitoring frameworks that quickly detect and resolve data quality and integrity issues before they impact analytics.
  • Strengthen data governance and compliance by implementing clear standards for metadata, access control, and data retention, making data easier to discover, secure, and use responsibly.
  • Accelerate analytics delivery by designing scalable, efficient data pipelines with built-in monitoring and alerting, reducing downtime and improving responsiveness to business needs.
  • Enhance system performance and efficiency by creating optimized physical data models, indexing strategies, and table relationships that reduce query times and resource usage.
  • Drive innovation through modern data architecture by leveraging cloud and distributed platforms (e.g., Data Lakes, NoSQL, Hadoop ecosystems) to support high-volume, high-velocity data processing.
  • Increase productivity through automation by eliminating repetitive manual tasks in data preparation and integration, reducing errors and freeing up teams for higher-value work.
  • Elevate team capability and delivery speed by mentoring teammates and applying Agile/DevOps practices, ensuring continuous improvement and successful execution of critical analytics initiatives

Responsibilities
To be successful in this role you will need the following:
  • System Requirements Engineering - Uses appropriate methods and tools to translate stakeholder needs into verifiable requirements to which designs are developed; establishes acceptance criteria for the system of interest through analysis, allocation and negotiation; tracks the status of requirements throughout the system lifecycle; assesses the impact of changes to system requirements on project scope, schedule, and resources; creates and maintains information linkages to related artifacts.
  • Collaborates - Building partnerships and working collaboratively with others to meet shared objectives.
  • Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
  • Customer focus - Building strong customer relationships and delivering customer-centric solutions.
  • Decision quality - Making good and timely decisions that keep the organization moving forward.
  • Data Extraction - Performs data extract-transform-load (ETL) activities from variety of sources and transforms them for consumption by various downstream applications and users using appropriate tools and technologies.
  • Programming - Creates, writes and tests computer code, test scripts, and build scripts using algorithmic analysis and design, industry standards and tools, version control, and build and test automation to meet business, technical, security, governance and compliance requirements.
  • Quality Assurance Metrics - Applies the science of measurement to assess whether a solution meets its intended outcomes using the IT Operating Model (ITOM), including the SDLC standards, tools, metrics and key performance indicators, to deliver a quality product.
  • Solution Documentation - Documents information and solution based on knowledge gained as part of product development activities; communicates to stakeholders with the goal of enabling improved productivity and effective knowledge transfer to others who were not originally part of the initial learning.
  • Solution Validation Testing - Validates a configuration item change or solution using the Function's defined best practices, including the Systems Development Life Cycle (SDLC) standards, tools and metrics, to ensure that it works as designed and meets customer requirements.
  • Data Quality - Identifies, understands and corrects flaws in data that supports effective information governance across operational business processes and decision making.
  • Problem Solving - Solves problems and may mentor others on effective problem solving by using a systematic analysis process by leveraging industry standard methodologies to create problem traceability and protect the customer; determines the assignable cause; implements robust, data-based solutions; identifies the systemic root causes and ensures actions to prevent problem reoccurrence are implemented.
  • Values differences - Recognizing the value that different perspectives and cultures bring to an organization.

Education, Licenses, Certifications:
  • College, university, or equivalent degree in relevant technical discipline, or relevant equivalent experience required.
  • This position may require licensing for compliance with export controls or sanctions regulations.

Experience:
Intermediate experience in a relevant discipline area is required. Knowledge of the latest technologies and trends in data engineering are highly preferred and includes:
- Familiarity analyzing complex business systems, industry requirements, and/or data regulations
- Background in processing and managing large data sets
- Design and development for a Big Data platform using open source and third-party tools
- SPARK, Scala/Java, Map-Reduce, Hive, Hbase, and Kafka or equivalent college coursework
- SQL query language
- Clustered compute cloud-based implementation experience
- Experience developing applications requiring large file movement for a Cloud-based environment and other data extraction tools and methods from a variety of sources
- Experience in building analytical solutions
Intermediate experiences in the following are preferred:
- Experience with IoT technology
- Experience in Agile software development
Qualifications
Core Responsibilities / Activities:
  • Design and implement scalable and efficient data pipelines using Apache Spark and Databricks on Azure.
  • Lead the complex transformation and integration of unstructured data sources into structured Delta Lake formats, applying software engineering best practices to ensure reliability, modularity, and reusability.
  • Troubleshoot and optimize Spark jobs for performance, reliability, and cost-efficiency in a production environment.
  • Drive continuous improvement of data engineering solutions by leveraging AI/ML and LLM-based techniques to enhance observability, performance optimization, and long-term maintainability.

Skill, Education, or Experience Requirements:
  • Minimum of 5 years of hands-on experience in data engineering with expertise in Azure Databricks and programming in Scala or Python.
  • Proven experience in building and maintaining structured streaming pipelines using Spark.
  • Strong knowledge of big data technologies, including Delta Lake, Apache Spark, Structured Streaming, and SQL.
  • Experience with Git for version control and CI/CD pipeline management.

Nice to Have (Preferences):
  • Data Engineering Certification (e.g., Databricks Certified Data Engineer, Apache Spark Professional Data Engineer, or equivalent).
  • Exposure to real-time data ingestion frameworks and cloud-native data services (e.g., Azure Event Hub, Azure Data Lake, AWS SQS, etc).
  • Familiarity with data governance, access control (e.g., Unity Catalog or Immuta), and performance monitoring tools in cloud environments.

About Us
Cummins is an equal opportunity employer. Our policy is to provide equal employment opportunities to all qualified persons without regard to race, sex, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity, or other status protected by law.

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About Cummins

Sourced by ZipRecruiter

Cummins Inc., headquartered in Columbus, IN, US, is a global power leader that designs, manufactures, and distributes numerous power products and systems. With its genesis from as early as 1919, the company readily serves diverse industries such as transportation, industrial, generator drive, or marine applications, among others. At the heart of Cummins' operations, its key product lineup encompasses diesel & natural gas engines, generator sets, engine components, and filtration, emission solutions, and electrical power generation systems. Cummins deeply embodies core values of integrity, respect for diversity, teamwork, performance excellence, and social responsibility - all of which dynamically fuel their mission 'Making people's lives better by powering a more prosperous world'.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Columbus, IN, US

Year founded

1919

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