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Data Engineer Jobs in Columbus, IN (NOW HIRING)

Virtusa Corporation

GCP Architect

Columbus, IN · On-site

$59.25 - $76.25/hr

Data Engineering & Modeling Data Modeling, Logical Data Modeling, Physical Data Modeling, Dimensional Data Modeling, Data Vault Modeling, Data Engineering, Enterprise Data Models, Data Pipelines ...

Circle K

Senior Manager Data Architecture

Columbus, IN

$62.50 - $83.75/hr

Join our Global Data Engineering, Architecture and Enablement team and help build the foundation for data-driven decisions across our entire enterprise. Location This is a full-time (5 days in office ...

MatchPoint Solutions

Senior Data Scientist

Columbus, IN · On-site

$80K - $90K/yr

MatchPoint Solutions is a fast-growing, young, energetic global IT-Engineering services company ... Senior Data Scientist Location: (Remote / Hybrid / On-site - City, Country) Columbus, IN Employment ...

Emids

Systems Engineer

Franklin, IN · On-site +1

Translate business requirements into technical requirements for data solutions. Work with engineering teams to design and build scalable reporting and data solutions, utilizing cloud platforms like ...

CYNET SYSTEMS

Data Analyst

Columbus, IN · On-site

$32 - $37/hr

Strong Power BI and data modeling experience. * Working knowledge of SQL, data integration, and ... We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and ...

USM

Data Scientist

Columbus, IN · On-site

... Product Engineering, Business Intelligence, Data Management, SOA, BPM, Data Warehousing, SharePoint Consulting and IT Infrastructure. Our other offerings include modified solutions and ...

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All JobsData Engineer JobsData Engineer Jobs in Columbus, IN

Data Engineer information

See Columbus, IN salary details

$41.4K

$120.6K

$165.1K

How much do data engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data engineer in Columbus, IN is $120,644.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,500.00 and $127,900.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

What are the key skills and qualifications needed to thrive as a data engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.
More about Data Engineer jobs

What are the most commonly searched types of Data Engineer jobs in Columbus, IN?

The most popular types of Data Engineer jobs in Columbus, IN are:

What are popular job titles related to Data Engineer jobs in Columbus, IN?

For Data Engineer jobs in Columbus, IN, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Columbus, IN look for?

The top searched job categories for Data Engineer jobs in Columbus, IN are:

What cities near Columbus, IN are hiring for Data Engineer jobs?

Cities near Columbus, IN with the most Data Engineer job openings:

Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Columbus, IN as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $120,644 per year, or $58 per hour.

Google Cloud Platform Data Architect

Columbus, IN • On-site

TekLeaders, Inc
See more jobs at TekLeaders, Incexternal

$59.25 - $76.25/hr

Other

Posted 7 days ago

Job description

Job Title: Google Cloud Platform Data Architect
Location: Columbus, Indiana (Hybrid)

Primary Skill : Cloud Google Cloud Platform, Data Modeling, Google Cloud Platform


12+ Years experience required

Job Description :

Data Engineering & Modeling Data Modeling, Logical Data Modeling, Physical Data Modeling, Dimensional Data Modeling, Data Vault Modeling, Data Engineering, Enterprise Data Models, Data Pipelines, Data Governance, Data Architecture, Data Mesh, Lakehouse Architecture Real-Time Data Processing Real-Time Data Pipelines, Streaming Data Processing, Event-Driven Architecture, Apache Kafka, Google Pub/Sub, Low-Latency Data Processing Google Cloud Platform (Google Cloud Platform)Google Cloud Platform, Big Query, Dataflow, Pub/Sub, Vertex AI, Cloud Architecture, Google Cloud Platform Professional Data Engineer, Google Cloud Platform Professional Cloud Architect AI, Machine Learning & MLOps Machine Learning, AI/ML Model Deployment, ML Inferencing, MLOps, Model Monitoring, Model Governance, Model Risk Management, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vector Databases, MLflow, Kube flow Cloud & Data Technologies Python, SQL, API Integration, Kubernetes, Docker, CI/CD, Apache Spark, Databricks, Snowflake Banking & Financial Domain Banking, Fraud Detection, Risk Management, AML, KYC, Regulatory Compliance, Data Compliance, Operationalizing AI/ML Models, Cross-Functional Collaboration, Data Science, Risk Analytics, Enterprise Solutions

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