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Internship Data Recovery Jobs (NOW HIRING)

ncmec

Make sound judgment calls that will aid in the location, recovery, and reunification of missing or ... Two years related work or internship experience preferred. * An equivalent combination of education ...

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Internship Data Recovery information

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How much do internship data recovery jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for internship data recovery in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is an internship in data recovery?

An Internship in Data Recovery is a temporary position where students or recent graduates learn how to recover lost, corrupted, or inaccessible data from various storage devices such as hard drives, SSDs, and USB drives. Interns typically assist experienced data recovery professionals with diagnostics, data retrieval processes, and customer support. This hands-on experience helps interns gain practical skills in using data recovery tools and software, understanding file systems, and learning best practices for handling sensitive data. The internship may also include training on data privacy and ethical considerations. Overall, it provides valuable industry exposure for those interested in IT, cybersecurity, or computer forensics.

What types of projects or tasks can an intern expect to work on in a data recovery internship?

As a data recovery intern, you can expect to support experienced technicians in retrieving lost or corrupted data from various storage devices, such as hard drives, SSDs, and memory cards. Typical tasks may include running diagnostic software, assisting with hardware repairs in cleanroom environments, documenting recovery processes, and helping to analyze the causes of data loss. You will likely work closely with other team members, gaining hands-on experience with industry-standard tools while learning best practices for data security and client confidentiality. This collaborative and technical environment offers a great opportunity for skill development and insight into potential career paths in digital forensics or IT support.

What are the key skills and qualifications needed to thrive as an internship data recovery specialist, and why are they important?

To thrive in an Internship Data Recovery role, you need foundational knowledge of computer systems, data storage devices, and basic understanding of file systems, often supported by coursework in information technology or computer science. Familiarity with data recovery tools such as EnCase, FTK, or open-source utilities, as well as experience with operating systems like Windows and Linux, is typically required. Analytical thinking, attention to detail, and strong problem-solving skills are essential soft skills for this position. These competencies are crucial for accurately retrieving lost data, minimizing data loss, and ensuring data integrity during recovery processes.

What is the difference between Internship Data Recovery vs Data Recovery Technician?

AspectInternship Data RecoveryData Recovery Technician
CredentialsTypically pursuing or recent graduate, no formal certification requiredRelevant certifications like CDR, Data Recovery Certification often preferred
Work EnvironmentTraining setting, supervised, entry-level tasksProfessional lab or repair shop, hands-on recovery work
Industry UsageInternship programs in data recovery companies or IT departmentsFull-time or part-time roles in data recovery services
Search & Comparison IntentLearning about entry-level opportunities in data recoveryUnderstanding professional roles and qualifications in data recovery

Internship Data Recovery positions are designed for students or recent graduates gaining initial experience, often in a supervised environment. Data Recovery Technicians are experienced professionals performing actual recovery tasks, often requiring certifications. The internship provides foundational knowledge, while the technician role involves hands-on, technical work in a professional setting.

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Internship Data Recovery jobs near you
Infographic showing various Internship Data Recovery job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, and 10% Part Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Staff+ Software Engineer, Data Infrastructure

Anthropic

San Francisco, CA • On-site

$134K - $162K/yr

Full-time

Re-posted 4 days ago

Job description

About the role

Data Infrastructure designs, operates, and scales secure, privacy-respecting systems that power data-driven decisions across Anthropic. Our mission is to provide data processing, storage, and access that are trusted, fast, and easy to use.

We're looking for infrastructure engineers who thrive working at the intersection of data systems, security, and scalability. You'll tackle diverse challenges ranging from building financial reporting pipelines to architecting access control systems to ensuring cloud storage reliability. This role offers the opportunity to work directly with data scientists, analysts, and business stakeholders while diving deep into cloud infrastructure primitives.

Responsibilities:

Within Data Infra, you may be matched to critical business areas including: 

  • Data Governance & Access Control: Design and implement robust access control systems ensuring only authorized users can access sensitive data. Build infrastructure for permission management, audit logging, and compliance requirements. Work on IAM policies, ACLs, and security controls that scale across thousands of users and systems.

  • Financial Data Infrastructure: Build and maintain data pipelines and warehouses powering business-critical reporting. Ensure data integrity, accuracy, and availability for complex financial systems, including third party revenue ingestion pipelines; manage the external relationships as needed to drive upstream dependencies. Own the reliability of systems processing revenue, usage, and business metrics.

  • Cloud Storage & Reliability: Architect disaster recovery, backup, and replication systems for petabyte-scale data. Ensure high availability and durability of data stored in cloud object storage (GCS, S3). Build systems that protect against data loss and enable rapid recovery.

  • Data Platform & Tooling: Scale data processing infrastructure using technologies like BigQuery, BigTable, Airflow, dbt, and Spark. Optimize query performance, manage costs, and enable self-service analytics across the organization.

You might be a good fit if you:
  • Have 10+ years (not including internships or co-ops) of experience in a Software Engineer role, building data infrastructure, storage systems, or related distributed systems
  • Have 3+ years (not including internships or co-ops) of experience leading large scale, complex projects or teams as an engineer or tech lead
  • Can set technical direction for a team, not just execute within it
  • Have deep experience with at least one of:
  • Strong proficiency in programming languages like Python, Go, Java, or similar
  • Experience with infrastructure-as-code (Terraform, Pulumi) and cloud platforms (GCP, AWS)
  • Can navigate complex technical tradeoffs between performance, cost, security, and maintainability
  • Have excellent collaboration skills - you work well with both technical and non-technical stakeholders
Strong candidates may also have:
  • Experience with security and compliance requirements (ITGC, GDPR, financial controls)
  • Background in data warehousing, ETL/ELT pipelines, or analytics infrastructure
  • Experience with Kubernetes, containerization, and cloud-native architectures
  • Track record of improving data reliability, availability, or cost efficiency at scale
  • Knowledge of column-oriented databases, OLAP systems, or big data processing frameworks
  • Experience working in fintech, financial services, or highly regulated environments
  • Security engineering background with focus on data protection and access controls
Technologies We Use:
  • Data: BigQuery, BigTable, Airflow, Cloud Composer, dbt, Spark, Segment, Fivetran
  • Storage: GCS, S3
  • Infrastructure: Terraform, Kubernetes, GCP, AWS
  • Languages: Python, Go, SQL

Deadline to apply: None. Applications will be reviewed on a rolling basis.

Apply