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Data Analyst Github Jobs in Springfield, OH (NOW HIRING)

Senior Data Engineer

Beavercreek, OH · On-site

$80K - $133K/yr

Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public ... as Git, GitHub, GitLab, Jenkins, or Azure DevOps. * Experience implementing data quality ...

Develop scripts for data analysis and model validation * Enhance overall efficiency in MBSE ... GitHub). * Systems Engineering Fundamentals: 0-3 years of experience in systems engineering ...

Develop scripts for data analysis and model validation * Enhance overall efficiency in MBSE ... GitHub). * Systems Engineering Fundamentals: 0-3 years of experience in systems engineering ...

Software Architect, Lead

Dayton, OH · On-site

$112.80 - $257/hr

... and enterprise data platforms. * Translate complex analytical workflows into robust ... Experience designing CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins). * Experience with ...

... data harvesting, automation, and API definition * Implement MBSE methodologies that align with ... Proficiency with Git-based development workflows (GitLab/GitHub) * Understanding of CI/CD pipelines ...

... data harvesting, automation, and API definition * Implement MBSE methodologies that align with ... Proficiency with Git-based development workflows (GitLab/GitHub) * Understanding of CI/CD pipelines ...

... data harvesting, automation, and API definition * Implement MBSE methodologies that align with ... Proficiency with Git-based development workflows (GitLab/GitHub) * Understanding of CI/CD pipelines ...

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Showing results 1-20

Data Analyst Github information

See Springfield, OH salary details

$30.6K

$74.4K

$122.5K

How much do data analyst github jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data analyst github in Springfield, OH is $74,438.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,300.00 and $87,400.00 per year, depending on experience, location, and employer.

What is a data analyst at GitHub?

Data Analysts on GitHub are professionals or contributors who use the platform to share, collaborate, and manage data analysis projects. They leverage GitHub to store datasets, share scripts and code (often in languages like Python or R), and document their analyses using tools like Jupyter Notebooks or Markdown. GitHub enables Data Analysts to version-control their work, collaborate with others through pull requests and issues, and showcase their portfolios to potential employers or collaborators.

How does a data analyst at GitHub typically collaborate with engineering and product teams?

At GitHub, Data Analysts frequently work alongside engineering and product teams to translate business questions into actionable data insights. They participate in cross-functional meetings, help define key metrics, and build dashboards or reports tailored to the needs of different stakeholders. Effective collaboration requires strong communication skills, as analysts must explain complex data findings to both technical and non-technical colleagues. This collaborative environment fosters continual learning and often provides opportunities to contribute to strategic decisions that impact the direction of products and features.

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

To thrive as a Data Analyst on GitHub, you need strong analytical skills, experience in statistics, and proficiency in data manipulation using languages like Python or SQL, often backed by a relevant degree. Familiarity with data visualization tools (e.g., Tableau, Power BI), Git version control, and GitHub workflows is essential, and certifications in data analysis or related fields are advantageous. Attention to detail, problem-solving, and effective communication are vital soft skills for collaborating on open-source projects and sharing insights. These competencies enable accurate data-driven decision-making, efficient project collaboration, and impactful contributions to the GitHub community.

What is the difference between Data Analyst Github vs Data Scientist?

AspectData Analyst GithubData Scientist
Required CredentialsBachelor's in Data Analytics, Statistics, or related field; proficiency in SQL, Excel, and visualization toolsBachelor's or Master's in Data Science, Computer Science, or related; knowledge of programming languages like Python or R, machine learning
Work EnvironmentCollaborates with teams to analyze data, create dashboards, and support decision-makingBuilds models, develops algorithms, and performs advanced statistical analysis
Employer & Industry UsageUsed across industries for reporting, data visualization, and business insightsApplied in AI, predictive modeling, and complex data analysis projects

While both roles involve working with data, Data Analyst Github focuses on data visualization, reporting, and supporting business decisions, often using tools like SQL and Excel. Data Scientists perform advanced analytics, build predictive models, and require programming skills in Python or R. The roles overlap in data handling but differ in complexity and technical depth.

What job categories do people searching Data Analyst Github jobs in Springfield, OH look for?

The top searched job categories for Data Analyst Github jobs in Springfield, OH are:

What cities near Springfield, OH are hiring for Data Analyst Github jobs?

Cities near Springfield, OH with the most Data Analyst Github job openings:

Senior Data Engineer

Guidehouse

Beavercreek, OH • On-site

$80K - $133K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 26 days ago


Guidehouse rating

8.0

Company rating: 8.0 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

35th of 72 rated business consultants


Job description

Job Family:

Data Science & Analysis


Travel Required:

Up to 10%


Clearance Required:

Ability to Obtain Public Trust

What You Will Do:

Guidehouse seeks a Senior Data Engineer to design, develop, and optimize modern data platforms, pipelines, and cloud-based analytics solutions. The ideal candidate will have hands-on experience building scalable data ecosystems, strong software engineering fundamentals, and the ability to lead technical efforts while collaborating with multidisciplinary teams to deliver mission-critical data solutions.

  • Design, develop, and maintain scalable data pipelines and ETL/ELT processes supporting analytics, reporting, and operational workloads.

  • Build and optimize data architectures, data models, and storage solutions across cloud and hybrid environments.

  • Develop and maintain data engineering solutions using Python, SQL, Spark, and related technologies.

  • Implement and support cloud-native data platforms leveraging AWS, Azure, Databricks, and other modern technologies.

  • Design and implement CI/CD pipelines and DevOps best practices for data engineering workflows.

  • Collaborate with architects, developers, analysts, and business stakeholders to translate requirements into technical solutions.

  • Lead data integration, migration, and modernization initiatives, including legacy system transformation efforts.

  • Ensure data quality, integrity, security, and governance standards are incorporated into solution designs.

  • Monitor, troubleshoot, and optimize data pipelines and production environments to ensure reliability and performance.

  • Mentor junior data engineers and support technical knowledge sharing across project teams.

  • Contribute to technical architecture discussions, technology evaluations, and engineering best practices.

  • Develop and maintain technical documentation including data flows, system designs, deployment procedures, and operational guides.

  • Role contingent upon contract award.


What You Will Need:

  • U.S. Citizenship or Green Card is required and must be able to OBTAIN and MAINTAIN a Federal or DHS "PUBLIC TRUST

  • Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or a related technical field.

  • THREE (3) or more years in data engineering, software engineering, analytics engineering, or a related discipline.

  • Experience in Python, SQL, and data processing frameworks such as Spark or PySpark.

  • Experience designing, developing, and supporting production-grade data pipelines and ETL/ELT processes.

  • Experience working with relational and non-relational databases, including data modeling and query optimization.

  • Experience with cloud platforms such as AWS and/or Azure.

  • Experience with Databricks, Snowflake, or similar large-scale data processing environments.

  • Experience implementing CI/CD pipelines and version control practices using tools such as Git, GitHub, GitLab, Jenkins, or Azure DevOps.

  • Experience implementing data quality, monitoring, and operational support processes.

  • Experience working within Agile software development environments.


What Would Be Nice To Have:

  • Experience supporting federal, healthcare, public health, or other highly regulated environments.

  • Familiarity with containerization technologies such as Docker and orchestration platforms such as Kubernetes.

  • Experience with AWS services such as S3, Redshift, Lambda, ECS, Glue, and SQS.

  • Strong analytical, troubleshooting, and problem-solving skills.

  • Ability to independently manage technical tasks and collaborate effectively across teams.

  • Excellent verbal and written communication skills.

  • Experience with Azure services such as Azure Data Factory, Synapse Analytics, Azure Functions, Cosmos DB, and Event Hub.

  • Familiarity with modern data lakehouse architectures and data governance frameworks.

  • Experience implementing Infrastructure-as-Code using Terraform, CloudFormation, or Bicep.

  • Experience with monitoring and observability tools such as CloudWatch, Splunk, Kibana, Datadog, or Elasticsearch.

  • Cloud, Databricks, Snowflake, or related technical certifications.

  • Experience supporting large-scale data modernization or migration programs.

  • Experience with machine learning data pipelines and AI-enabled solutions.

  • Previous consulting or client-facing experience.

The annual salary range for this position is $80,000.00-$133,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs.


What We Offer:

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

Benefits include:

  • Medical, Rx, Dental & Vision Insurance

  • Personal and Family Sick Time & Company Paid Holidays

  • Parental Leave

  • 401(k) Retirement Plan

  • Group Term Life and Travel Assistance

  • Voluntary Life and AD&D Insurance

  • Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts

  • Transit and Parking Commuter Benefits

  • Short-Term & Long-Term Disability

  • Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities

  • Employee Referral Program

  • Corporate Sponsored Events & Community Outreach

  • Care.com annual membership

  • Employee Assistance Program

  • Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)

  • Position may be eligible for a discretionary variable incentive bonus

About Guidehouse

Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.

Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.

If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation.

All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process.

If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties.

Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.


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