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Data Retrieval Jobs (NOW HIRING)

My3Tech Inc

Data Engineer

Cincinnati, OH

$109K - $132K/yr

Ensure efficient data retrieval and augmentation processes to support LLM training and inference. * Collaborate with data scientists to optimize data pipelines for LLM performance and accuracy.

Prophecy Technologies

Data Fabric Architect

Phoenix, AZ · On-site

$63.25 - $81.50/hr

Deep understanding of Generative AI architectures and Retrieval-Augmented Generation (RAG) pipelines * Strong background in data modeling, semantic layers, and metadata management * Proficiency in ...

DCS Corp

Avionics Data Engineer

Lexington Park, MD · On-site

$90K - $140K/yr

Operate independently and as part of multiple larger teams to evaluate vendor solutions for US Navy aircraft data storage, data retrieval, and data processing. Required Skills: Due to the sensitivity ...

Intrepidgs

Data Warehousing Administrator

Mclean, VA · On-site

Ensure data integrity and efficient data retrieval. * Implement long-term security protections for stored data. * Operate independently across multiple work areas. * Lead major technical assignments ...

DCS CORPORATION

Avionics Data Engineer

Patuxent River, MD · On-site

$90K - $140K/yr

Operate independently and as part of multiple larger teams to evaluate vendor solutions for US Navy aircraft data storage, data retrieval, and data processing. Required Skills: Due to the sensitivity ...

Intrepid

Data Warehousing Administrator

Mclean, VA · On-site

Ensure data integrity and efficient data retrieval. * Implement long-term security protections for stored data. * Operate independently across multiple work areas. * Lead major technical assignments ...

Quantiphi, Inc.

Architect Data Engineer

Boston, MA · On-site +1

Establish benchmarks for data latency and retrieval accuracy, ensuring the data layer can keep pace with the real-time demands of agentic executionrability standards Basic Qualifications: * System ...

Quantiphi, Inc.

Architect Data Engineer

Boston, MA · On-site

Establish benchmarks for data latency and retrieval accuracy, ensuring the data layer can keep pace with the real-time demands of agentic executionrability standards Basic Qualifications: * System ...

DCS Corporation

Avionics Data Engineer

Patuxent River, MD · On-site

$90K - $140K/yr

Operate independently and as part of multiple larger teams to evaluate vendor solutions for US Navy aircraft data storage, data retrieval, and data processing. Required Skills: Due to the sensitivity ...

Prophecy Technologies

ClickHouse Data Engineer

Bentonville, AR · On-site

$100K - $120K/yr

Write and optimize complex SQL queries for fast data retrieval and analytical workloads * Build and manage data ingestion pipelines using tools such as Kafka, Spark, or ETL frameworks * Monitor and ...

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How much do data retrieval jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for data retrieval in the United States is $25.82, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $25.24 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Retrieval Specialist, and why are they important?

To thrive as a Data Retrieval Specialist, a strong background in database management, data analysis, and information systems—often supported by a relevant degree—is essential. Familiarity with SQL, data extraction tools, and enterprise database systems such as Oracle or Microsoft SQL Server is typically required. Attention to detail, problem-solving abilities, and clear communication skills help professionals interpret requirements and ensure data accuracy. These competencies are crucial for efficiently locating, extracting, and validating data to support business decision-making and compliance.

What jobs make $1,000,000 a year?

In the field of data retrieval, high-earning roles such as chief data officers, data science executives, or senior data consultants can reach or exceed $1 million annually, especially in large corporations or tech firms. These positions often require extensive experience, advanced skills in data management and analytics, and leadership responsibilities. Compensation at this level may include base salary, bonuses, stock options, and other incentives.

What is data retrieval?

Data retrieval is the process of obtaining and extracting specific information from a database, storage system, or other data sources. It involves using queries or search techniques to locate and access relevant data efficiently and accurately. Data retrieval is essential in fields like data analysis, information management, and business intelligence, as it helps organizations make informed decisions based on up-to-date information. Professionals in this area often use tools and programming languages such as SQL, Python, or specialized data management software to streamline the retrieval process.

What is the difference between Data Retrieval vs Data Analyst?

AspectData RetrievalData Analyst
Primary RoleExtracting data from databases or sourcesInterpreting, analyzing, and visualizing data
Skills & CertificationsSQL, database managementSQL, statistics, data visualization tools
Work EnvironmentDatabase systems, data warehousesAnalytics platforms, reporting tools
Industry UsageIT, database management, data engineeringBusiness intelligence, marketing, finance

Data Retrieval focuses on extracting data efficiently from sources, while Data Analysts interpret and analyze that data to support decision-making. Both roles often collaborate but serve different functions within data management and analysis processes.

How to get a job in data recovery?

To get a job in data recovery, candidates typically need a background in computer science, information technology, or a related field, along with skills in data storage devices, file systems, and troubleshooting. Certifications such as CompTIA A+ or specialized training in data recovery tools can improve employability. Experience with hardware repair, data recovery software, and understanding of data security are also valuable for this role.

What are some common challenges faced in a Data Retrieval role and how can they be addressed?

Professionals in Data Retrieval often encounter challenges such as dealing with large, unstructured datasets, ensuring data accuracy, and maintaining data security. Addressing these issues typically requires proficiency with advanced query languages, data cleaning tools, and strong attention to detail. Collaborating closely with data engineers and analysts can also help in developing efficient retrieval processes and verifying data integrity. Continuous learning and staying updated with the latest tools and best practices are crucial for overcoming these challenges effectively.

What job makes $10,000 a month without a degree?

A data retrieval specialist or similar roles in data analysis and information management can potentially earn $10,000 or more per month through freelance work, consulting, or high-demand positions that require strong technical skills and experience. These roles often involve working with databases, data mining tools, and programming languages like SQL or Python, and may not require a formal degree but do demand expertise and proven ability to deliver results.

Is 40 too late for data science?

Data retrieval roles and data science careers do not have strict age limits; many professionals transition into these fields later in life. Success depends on acquiring relevant skills such as programming, statistics, and tools like SQL or Python, regardless of age. Continuous learning and practical experience are key factors for career advancement in data-related jobs.
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What job categories do people searching Data Retrieval jobs look for? The top searched job categories for Data Retrieval jobs are:
Data Retrieval jobs near you
Infographic showing various Data Retrieval job openings in the United States as of June 2026, with employment types broken down into 6% As Needed, 13% Full Time, and 81% Part Time. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $53,700 per year, or $25.8 per hour.
Data Engineer

Data Engineer

My3Tech Inc

Cincinnati, OH

$109K - $132K/yr

Other

Posted 11 days ago

Job description

We are seeking a skilled Data Engineer to join our Data Science team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support data analytics, machine learning, and Retrieval-Augmented Generation (RAG) type Large Language Model (LLM) workflows. This role requires a strong technical background, excellent problem-solving skills, and the ability to work collaboratively with data scientists, analysts, and other stakeholders.
Key Responsibilities:

  1. Data Pipeline Development:
    • Design, develop, and maintain robust and scalable ETL (Extract, Transform, Load) processes.
    • Ensure data is collected, processed, and stored efficiently and accurately.
  2. Data Integration:
    • Integrate data from various sources, including databases, APIs, and third-party data providers.
    • Ensure data consistency and integrity across different systems.
  3. RAG Type LLM Workflows:
    • Develop and maintain data pipelines specifically tailored for Retrieval-Augmented Generation (RAG) type Large Language Model (LLM) workflows.
    • Ensure efficient data retrieval and augmentation processes to support LLM training and inference.
    • Collaborate with data scientists to optimize data pipelines for LLM performance and accuracy.
  4. Semantic/Ontology Data Layers:
    • Develop and maintain semantic and ontology data layers to enhance data integration and retrieval.
    • Ensure data is semantically enriched to support advanced analytics and machine learning models.
  5. Collaboration:
    • Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
    • Provide technical support and guidance on data-related issues.
  6. Data Quality and Governance:
    • Implement data quality checks and validation processes to ensure data accuracy and reliability.
    • Adhere to data governance policies and best practices.
  7. Performance Optimization:
    • Monitor and optimize the performance of data pipelines and infrastructure.
    • Troubleshoot and resolve data-related issues in a timely manner.
  8. Support for Analysis:
    • Support short-term ad-hoc analysis by providing quick and reliable data access.
    • Contribute to longer-term goals by developing scalable and maintainable data solutions.
  9. Documentation:
    • Maintain comprehensive documentation of data pipelines, processes, and infrastructure.
    • Ensure knowledge transfer and continuity within the team.
Technical Requirements:
  1. Education and Experience:
    • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
    • 3+ years of experience in data engineering or a related role.
  2. Technical Skills:
    • Proficiency in Python (mandatory).
    • Experience with other programming languages such as Java or Scala is a plus.
    • Experience with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB).
    • Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka).
    • Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
  3. RAG Type LLM Skills:
    • Experience with data pipelines for LLM workflows, including data retrieval and augmentation.
    • Familiarity with natural language processing (NLP) techniques and tools.
    • Understanding of LLM architectures and their data requirements.
  4. Semantic/Ontology Data Layers:
    • Familiarity with semantic and ontology data layers and their application in data integration and retrieval.
  5. Tools and Frameworks:
    • Experience with ETL tools and frameworks (e.g., Apache NiFi, Airflow, Talend).
    • Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
  6. Soft Skills:
    • Strong analytical and problem-solving skills.
    • Excellent communication and collaboration abilities.
    • Ability to work in a fast-paced, dynamic environment.

Preferred Qualifications:
  • Experience with machine learning and data science workflows.
  • Knowledge of data governance and compliance standards.
  • Certification in cloud platforms or data engineering.

Required Skills : Must be local to Cincinnati
Basic Qualification :
Additional Skills :
Background Check : Yes
Drug Screen : Yes
Notes :
Selling points for candidate :
Project Verification Info :
Candidate must be your W2 Employee :Yes
Exclusive to Apex :No
Face to face interview required :No
Candidate must be local :Yes
Candidate must be authorized to work without sponsorship :Yes
Interview times set : :No
Type of project :
Master Job Title :
Branch Code :

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