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Big Data Software Engineer Jobs in Ohio (NOW HIRING)

Chase

AWS Big Data Lead Software Engineer

Columbus, OH · On-site

$52 - $69/hr

Software Engineer Design & build new applications utilizing leading edge technologies and modernize ... Experience with Big Data / Distributed / cloud technology (AWS Big data services like lambda, glue ...

Georgia IT Inc

Sr Software Engineer -Hybrid

Columbus, OH · Hybrid

$114K - $150K/yr

Sr Software Engineer Location: Columbus, Ohio (Hybrid Onsite - 3 Days/Week) Duration: 6-12 Months ... This individual will be responsible for migrating Big Data workloads to Kubernetes/Spark 3. This ...

CAS

Software Engineer

Columbus, OH · Hybrid

Software Engineer CAS uses unparalleled scientific content, specialized technology and unmatched ... Experience with Big Data technologies such as Hadoop, Spark, and Scala is desirable. * Familiarity ...

Prophecy Technologies

Data Engineer - GCP

Dublin, OH · On-site

$110K - $132K/yr

Job Summary The Senior Data Engineer will design, build, optimize, and support enterprise-scale data pipelines within a hybrid big data architecture , primarily on Google Cloud Platform (GCP) . This ...

ComResource

Data Engineer

Cincinnati, OH

$109K - $131K/yr

Evaluate software products and provide documented recommendations as needed. * Provide support and ... Conceptual understanding of one or more of the following: big data technologies and distributions ...

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Big Data Software Engineer information

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How much do big data software engineer jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for big data software engineer in Ohio is $59.88, according to ZipRecruiter salary data. Most workers in this role earn between $50.96 and $67.40 per hour, depending on experience, location, and employer.

What is a Big Data Software Engineer?

A Big Data Software Engineer is a technology professional who designs, develops, and maintains systems and applications that process large and complex data sets. They work with big data technologies like Hadoop, Spark, and NoSQL databases to enable efficient data storage, processing, and analysis. These engineers collaborate with data scientists, analysts, and other stakeholders to build scalable solutions that extract valuable insights from massive amounts of data. Their work is essential in industries such as finance, healthcare, e-commerce, and more, where data-driven decision-making is critical.

What Does a Big Data Software Engineer Do?

As a big data software engineer, your primary responsibilities are to collect, store, process, and analyze large amounts of data. You then build what the software architects design. Your duties are to develop software and choose solutions to maintain, implement, and continue monitoring the data. You also need to integrate your code with the current company architecture. You may handle high scale distributed systems, build and interact with algorithms, and work in cloud computing environments.

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

To thrive as a Big Data Software Engineer, you need strong programming skills (often in Java, Scala, or Python), a solid understanding of distributed systems, and a degree in computer science or related field. Experience with big data tools like Hadoop, Spark, Kafka, as well as familiarity with cloud platforms and data pipeline frameworks, is typically required. Problem-solving, analytical thinking, and effective teamwork are essential soft skills for handling complex data challenges and collaborating across teams. These skills and qualifications are crucial for designing efficient, scalable data solutions that drive business insights and innovation.

What is the difference between Big Data Software Engineer vs Data Engineer?

AspectBig Data Software EngineerData Engineer
Primary FocusDeveloping and optimizing big data processing applicationsBuilding and maintaining data pipelines and infrastructure
Skills & CertificationsProgramming (Java, Scala), Hadoop, Spark, SQLETL tools, SQL, cloud platforms, scripting
Work EnvironmentData processing teams, software development projectsData infrastructure teams, cloud environments
Industry UsageTech, finance, healthcare, retailTech, finance, healthcare, retail

While both roles work with big data technologies, Big Data Software Engineers focus on creating scalable data processing applications, whereas Data Engineers build and maintain the data pipelines and infrastructure that support these applications. Both roles often collaborate but have distinct technical responsibilities.

What are the most common challenges Big Data Software Engineers face when working with large-scale data systems?

Big Data Software Engineers often encounter challenges such as ensuring data quality, optimizing the performance of data pipelines, and managing the complexity of distributed systems. Handling massive volumes of data requires careful attention to system scalability and fault tolerance. Additionally, integrating new technologies and collaborating with data scientists, analysts, and DevOps teams to deploy and maintain reliable data solutions are key aspects of the role. Staying updated on evolving big data frameworks and best practices is crucial for continued success.
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Big Data Software Engineer jobs near you

AWS Big Data Lead Software Engineer

JPMorganChase

Columbus, OH • On-site

$53.75 - $71.25/hr

Full-time

Posted 27 days ago

Job description

Job Summary:
JPMorganChase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals. They are seeking an AWS Big Data Lead Software Engineer to design and build applications utilizing modern technologies, ensure code quality, and collaborate with agile teams to meet project objectives.
Responsibilities:
• Design & build new applications utilizing leading edge technologies and modernize existing applications
• Implement batch & real-time software components consistent with architectural best-practices of reliability, security, operational efficiency, cost-effectiveness and performance
• Ensure quality of deployed code via automated unit, integration & acceptance testing
• Collaborate with multi-national agile development, support and business teams to meet sprint objectives
• Participate in all agile meetings & rituals, including daily standups, sprint planning, backlog reviews, demos, and retrospectives
• Provide level 2 support for production systems
• Learn and applies system processes, methodologies, and skills for the development of secure, stable code and systems
• Hands on applicaitn development leveraging distributed compute such as Apache flink or Spark on very large datasets
• Design and development of applications that leverage the AWS infrastructure deploying software components on AWS using common compute and storage services such as EC2, EKS, Lambda, S3
• Lead and deliver projects from concept to production across PNI (Personalization and Insights) platform
Qualifications:
Required:
• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience in Frameworks, system design, application development, testing, and operational stability
• Experience with Apache Spark, Apache Flink or similar large-scale data processing engines
• Experience with Distributed Datastores (e.g. Cassandra, Red Shift)
• Experience designing, developing and deploying software components on AWS using common compute and storage services such as EC2, EKS, Lambda, S3
• Experience with Big Data / Distributed / cloud technology (AWS Big data services like lambda, glue, glue emr, Performance tuning, Streaming, KAFKA, Entitlements etc.)
• Experience with Apache Spark, Ray or similar large-scale data processing engines
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, BigData, artificial intelligence, machine learning, mobile, etc.)
Preferred:
• Experience building ETL/Feature processing pipelines
• Experience using workflow orchestration tools—Airflow, Kubeflow etc.
• Experience using Terraform to deploy infrastructure-as-code to public cloud
• Experience with Linux scripting such as Bash, KSH, or Python
• Certified AWS Cloud Practitioner, Developer or Solutions Architect strongly preferred
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.

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