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Data Recovery Jobs in Atlanta, GA (NOW HIRING)

nLeague Services Inc

Data Scientist

Atlanta, GA · On-site

... and maintain data recovery and contingency plans in case of system failure or other disruptions. Decision Making * Selects from multiple procedures and methods to accomplish tasks. Follows ...

NV5

Project Archaeologist

Alpharetta, GA · On-site

The archaeologist will conduct research, field surveys, and data recovery initiatives to assist in the identification and evaluation of archaeological sites and will complete project tasks within ...

NV5

Project Archaeologist

Alpharetta, GA · On-site +1

The archaeologist will conduct research, field surveys, and data recovery initiatives to assist in the identification and evaluation of archaeological sites and will complete project tasks within ...

NV5

Project Archaeologist

Alpharetta, GA · On-site +1

The archaeologist will conduct research, field surveys, and data recovery initiatives to assist in the identification and evaluation of archaeological sites and will complete project tasks within ...

Dragados

Senior IT Support Specialist

Brookhaven, GA · On-site

Conduct regular backups to prevent data loss and perform data recovery if needed. * Monitor systems for potential security threats and ensure network security. Training and documentation * Train ...

Agile Consulting Group, Inc.

Data Analyst

Norcross, GA · On-site

We are seeking a Data Analyst to join our tax recovery team, focusing on sales tax refund reviews . The ideal candidate will analyze transaction-level data, identify overpaid taxes, and support the ...

NV5

Archaeological Technician

Alpharetta, GA · On-site

Conduct evaluative test or data recovery excavations. The Field Technician will carry out archaeological block excavations, including digging and screening of soil, recovering artifacts and samples ...

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How much do data recovery jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for data recovery in Atlanta, GA is $26.53, according to ZipRecruiter salary data. Most workers in this role earn between $15.71 and $39.27 per hour, depending on experience, location, and employer.

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

To thrive in Data Recovery, you need expertise in data storage systems, file structures, and troubleshooting techniques, often supported by a degree in information technology or a related field. Familiarity with industry-standard recovery tools such as EnCase, R-Studio, and forensic software, along with relevant certifications like Certified Data Recovery Professional (CDRP), is highly valued. Strong analytical thinking, attention to detail, and effective communication are essential soft skills for diagnosing problems and interacting with clients. These competencies are vital for successfully retrieving lost data, maintaining data integrity, and ensuring customer satisfaction under often time-sensitive conditions.

What are the most common challenges faced in a data recovery role?

Professionals in Data Recovery often encounter challenges such as working with severely damaged hardware, complex data loss scenarios, or dealing with encryption and proprietary file systems. These situations require both technical proficiency and creative problem-solving to recover as much data as possible without compromising its integrity. Additionally, managing client expectations and clearly communicating recovery outcomes are important aspects of the job. Team members may collaborate with IT support staff, security professionals, or legal teams to address various cases. These challenges make the work dynamic and rewarding for those who enjoy solving technical puzzles and providing critical support to clients.

What is a data recovery?

A Data Recovery job involves retrieving lost, corrupted, or inaccessible data from storage devices like hard drives, SSDs, USB drives, and memory cards. Professionals in this field use specialized software and hardware tools to recover files that may have been deleted, damaged, or lost due to system failures, malware, or physical damage. They also assess storage media, implement recovery strategies, and ensure data integrity. Many data recovery specialists work for IT services, forensic teams, or businesses that require critical data restoration.

What are the most commonly searched types of Data Recovery jobs in Atlanta, GA? The most popular types of Data Recovery jobs in Atlanta, GA are:
What are popular job titles related to Data Recovery jobs in Atlanta, GA? For Data Recovery jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Data Recovery jobs in Atlanta, GA look for? The top searched job categories for Data Recovery jobs in Atlanta, GA are:
Data Recovery jobs near you
Infographic showing various Data Recovery job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $55,186 per year, or $26.5 per hour.

Data Scientist

nLeague Services Inc

Atlanta, GA • On-site

Contractor

Re-posted 12 days ago

Job description

Job ID: 65041
Data Scientist
Client: City of Atlanta- Aviation
Duration: 
Location: 6000 N. Terminal Pkwy, Atlanta, GA 30320
Onsite
 
General Description and Classification Standards 
The Data Scientist is responsible for maintaining and enhancing the organization's data infrastructure, creating advanced analytics solutions, and leveraging machine learning to improve decision-making and business efficiency. You will oversee the deployment, configuration, and continuous improvement of data models and infrastructure, ensuring robust performance and data security. In this role, you will work collaboratively with cross-functional teams to achieve organizational goals, offering innovative data-driven insights and solutions.
Supervision Received 
Works under minimal supervision. May work independently with responsibility for specific functions or programs. Expected to take a lead role in guiding data strategy and mentoring junior data scientists or analysts.
Essential Duties & Responsibilities 
  • Fully support, configure, maintain, and upgrade networks and servers at the Department of Aviation
  • Model Development and Optimization: Design, build, and refine predictive models and algorithms to enhance decision-making and drive business value.
  • Data Infrastructure Management: Maintain and optimize data pipelines, ensuring data integrity, security, and performance across the organization.
  • Data Strategy & Research: Research and propose cutting-edge data science techniques and methodologies to improve existing processes and introduce new data-driven initiatives.
  • Advanced Analytics & Insights: Provide deep analytical insights to solve complex business problems using statistical models, machine learning, and artificial intelligence.
  • Collaboration: Work with stakeholders across various departments (e.g., marketing, finance, operations) to understand data needs and deliver tailored analytics solutions.
  • Network & System Optimization: Ensure the organization’s data systems and models are operating at optimal levels, performing regular updates and improvements.
  • Performance Monitoring: Oversee the monitoring of data model performance, ensuring accuracy, scalability, and stability.
  • Technical Documentation: Write and maintain comprehensive documentation for all data science projects, including system architecture, model performance, and experiment results.
  • Customer-Focused Approach: Deliver clear, actionable insights to non-technical stakeholders, supporting business units in leveraging data for enhanced decision-making.
  • Mentorship: Act as a technical resource and mentor for junior data scientists and data analysts, guiding them in best practices, troubleshooting, and project execution.
Essential Duties & Responsibilities 
Support:
·    Respond to and resolve complex data-related issues, collaborating with IT support teams as necessary.
·    Ensure compliance with data governance and security standards.
·    Provide recommendations for improving data infrastructure and processes to increase business efficiency.
·    Deliver ongoing support for mission-critical business functions through data-driven strategies.
·    Develop and maintain data recovery and contingency plans in case of system failure or other disruptions.
Decision Making 
  • Selects from multiple procedures and methods to accomplish tasks. Follows standardized procedures and written instructions to accomplish assigned tasks.
  • Selects appropriate data science methodologies and tools to achieve business goals.
  • Exercises judgment in balancing short-term project deliverables with long-term data strategy.
  • Influences business decisions by providing actionable insights based on thorough data analysis.
Leadership Provided
  • Serves as a technical resource or mentor to other employees. May lead or instruct less experienced workers in high level or technical jobs.
  • Acts as a technical leader in the data science team, providing guidance and mentorship to less experienced team members.
  • Contributes to the strategic direction of the data science function within the organization.
  • Presents insights and findings to upper management, recommending improvements to data strategy and network infrastructure.
Knowledge, Skills & Abilities 
  • Technical Expertise: Deep knowledge of machine learning, artificial intelligence, data mining, and predictive analytics. Proficient in Python, R, SQL, and common machine learning frameworks (e.g., TensorFlow, Scikit-learn).
  • Data Infrastructure: Strong experience working with big data tools (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Problem-Solving: Ability to design and implement innovative solutions to complex problems, leveraging data to drive business improvements.
  • Communication: Excellent oral and written communication skills with the ability to explain complex technical concepts to non-technical audiences.
  • Collaboration: Proven ability to work across departments and manage multiple projects or tasks concurrently.
  • Leadership: Experience leading and mentoring teams, guiding them toward achieving technical excellence.
  • Security and Compliance: Familiarity with data security best practices, ensuring compliance with industry standards.
Non-Technical Skills
  • Project Management: Capable of managing multiple projects simultaneously while meeting deadlines and maintaining high standards of quality.
  • Self-Motivation: Uses initiative and independent judgment to undertake activities with minimal supervision.
  • Adaptability: Responds constructively to new information, changing conditions, and unexpected challenges.
  • Customer Service: Focuses on delivering value-driven, responsive solutions to both internal and external stakeholders.
 
Qualifications:
 Minimum Qualifications
Education and Experience 
  • Education: Bachelor’s degree in Data Science, Computer Science, Mathematics, or a related field equivalent professional experience may be considered.
  • Experience: 5+ years of experience in data science, data engineering, or related fields with hands-on experience in deploying machine learning models.
Preferred Education & Experience
  • Master’s or PhD in Data Science, Machine Learning, Computer Science, or a related field.
  • Experience in leading data science teams or large-scale projects within an enterprise setting.
  • Experience with Databricks, including designing, deploying, and optimizing machine learning models in the Databricks environment.
  • Expertise in cloud platforms, especially Azure and AWS, including experience with data storage, model deployment, and scaling cloud-based solutions.
  • Experience with Environmental Systems Research Institute (ESRI) and geographic information system (GIS) analytics, with a focus on spatial data analysis and location-based insights.
  • Strong background in Azure Data Services (e.g., Azure Data Lake, Azure Machine Learning) and AWS Machine Learning Services (e.g., SageMaker, Redshift, Lambda)..
Certifications
Relevant certifications in machine learning, data science, cloud computing, or network administration (e.g., AWS Certified Data Analytics, DataBricks, Microsoft Azure Data Scientist Associate) are highly desirable