Sr. AWS Data Architect
$66.25 - $87/hr
... data retrieval and management. • Provide technical guidance and support to team members fostering a collaborative and knowledge-sharing environment. • Ensure compliance with data security and ...
Sr. AWS Data Architect
$66.25 - $87/hr
... data retrieval and management. • Provide technical guidance and support to team members fostering a collaborative and knowledge-sharing environment. • Ensure compliance with data security and ...
Data Architect
Leesburg, VA · On-site +1
$64.50 - $83/hr
Architect modern AI-enabled data platforms, including support for machine learning, LLM integration, and retrieval-augmented generation (RAG) patterns. * Develop and maintain conceptual, logical, and ...
Data Architect
Leesburg, VA · On-site +1
$64.50 - $83/hr
Architect modern AI-enabled data platforms, including support for machine learning, LLM integration, and retrieval-augmented generation (RAG) patterns. * Develop and maintain conceptual, logical, and ...
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
Implement RESTful and GraphQL APIs for data retrieval and integration between Data Lake, ESRI ArcGIS, and external sources. Manage CI/CD pipelines, containerized deployments in Kubernetes, and API ...
Implement RESTful and GraphQL APIs for data retrieval and integration between Data Lake, ESRI ArcGIS, and external sources. Manage CI/CD pipelines, containerized deployments in Kubernetes, and API ...
Data Entry Operator (1)
Austin, TX · On-site
Generate routine reports and assist in data retrieval as requested. * Adhere to data privacy laws and hospital confidentiality standards at all times. * Perform regular backups to ensure data ...
Data Entry Operator (1)
Austin, TX · On-site
Generate routine reports and assist in data retrieval as requested. * Adhere to data privacy laws and hospital confidentiality standards at all times. * Perform regular backups to ensure data ...
Data Architect
Leesburg, VA · Remote
$65.25 - $84/hr
Architect modern AI-enabled data platforms, including support for machine learning, LLM integration, and retrieval-augmented generation (RAG) patterns. * Develop and maintain conceptual, logical, and ...
Quick apply
Data Architect
Leesburg, VA · Remote
$65.25 - $84/hr
Architect modern AI-enabled data platforms, including support for machine learning, LLM integration, and retrieval-augmented generation (RAG) patterns. * Develop and maintain conceptual, logical, and ...
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
The Lead Data Scientist will provide technical leadership to a team, driving the development of AI solutions for national security clients, focusing on knowledge retrieval and advanced analytics.
The Lead Data Scientist will provide technical leadership to a team, driving the development of AI solutions for national security clients, focusing on knowledge retrieval and advanced analytics.
This crucial position is key to building a strong culture of advanced agentic search, deep research, retrieval, and AI, and to creating scalable AI platforms for the wider AI and Data Science ...
Quick apply
This crucial position is key to building a strong culture of advanced agentic search, deep research, retrieval, and AI, and to creating scalable AI platforms for the wider AI and Data Science ...
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
Azure Data Engineer + Microsoft Fabric
Roswell, GA · On-site
$50.50 - $62.75/hr
... data retrieval and manipulation (e.g., SQL or KQL)
Quick apply
Azure Data Engineer + Microsoft Fabric
Roswell, GA · On-site
$50.50 - $62.75/hr
... data retrieval and manipulation (e.g., SQL or KQL)
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
This role implements RESTful and GraphQL APIs for seamless data retrieval and integration between Data Lake, ESRI ArcGIS, and external sources. This future opportunity is contingent upon award. • ...
This role implements RESTful and GraphQL APIs for seamless data retrieval and integration between Data Lake, ESRI ArcGIS, and external sources. This future opportunity is contingent upon award. • ...
Data Engineer
Baton Rouge, LA · On-site
$110K - $132K/yr
The Data Engineer will manage data retrieval, storage, and distribution across various platforms, ensuring the effectiveness of modern data architectures and contributing to business growth.
New
Data Engineer
Baton Rouge, LA · On-site
$110K - $132K/yr
The Data Engineer will manage data retrieval, storage, and distribution across various platforms, ensuring the effectiveness of modern data architectures and contributing to business growth.
New
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring.
Data Engineer
Lincoln, NE · On-site
$99K - $119K/yr
The Data Engineer role involves managing data retrieval, storage, and distribution across various platforms, focusing on modern ETL/ELT pipelines and data modeling to support business growth and ...
New
Data Engineer
Lincoln, NE · On-site
$99K - $119K/yr
The Data Engineer role involves managing data retrieval, storage, and distribution across various platforms, focusing on modern ETL/ELT pipelines and data modeling to support business growth and ...
New
... retrieval, and deep research systems. • Drive the expansion of data-driven research and advanced analytics for strategic business and national security results. • Design and deploy Agentic AI ...
... retrieval, and deep research systems. • Drive the expansion of data-driven research and advanced analytics for strategic business and national security results. • Design and deploy Agentic AI ...
Data Retrieval information
See salary details
$9.86 - $15.14
22% of jobs
$15.46 is the 25th percentile. Wages below this are outliers.
$15.14 - $20.43
48% of jobs
$22.48 is the 75th percentile. Wages above this are outliers.
$20.43 - $25.72
12% of jobs
$25.72 - $31.01
3% of jobs
$31.01 - $36.30
3% of jobs
$36.30 - $41.59
2% of jobs
$41.59 - $46.88
2% of jobs
$46.88 - $52.16
2% of jobs
$52.16 - $57.45
2% of jobs
$57.45 - $62.74
2% of jobs
$62.74 - $68.03
1% of jobs
$9
$25
$68
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?
| Aspect | Data Retrieval | Data Analyst |
|---|---|---|
| Primary Role | Extracting data from databases or sources | Interpreting, analyzing, and visualizing data |
| Skills & Certifications | SQL, database management | SQL, statistics, data visualization tools |
| Work Environment | Database systems, data warehouses | Analytics platforms, reporting tools |
| Industry Usage | IT, database management, data engineering | Business 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.
More about Data Retrieval jobs
What job categories do people searching Data Retrieval jobs look for? The top searched job categories for Data Retrieval jobs are:
Cognizant rating
7.5
Based on 83 frontline employees who took The Breakroom Quiz
37th of 57 rated business consultants
Job description
Job Summary:
Cognizant is looking for a Sr. AWS Data Architect who will optimize data processes and contribute to innovative solutions that drive the company's success. The role involves implementing AWS DevOps practices, managing ETL workflows, and ensuring data security and compliance.
Responsibilities:
• Implement AWS DevOps practices to streamline deployment and operational processes ensuring seamless integration and delivery.
• Utilize AWS Glue Studio to design and manage ETL workflows facilitating efficient data transformation and movement.
• Leverage AWS Glue ETL to automate data extraction transformation and loading processes improving data accessibility and usability.
• Manage AWS Glue Catalog to maintain a comprehensive and organized metadata repository ensuring data consistency and discoverability.
• Oversee Amazon S3 storage solutions to ensure secure and scalable data storage enabling efficient data retrieval and management.
• Provide technical guidance and support to team members fostering a collaborative and knowledge-sharing environment.
• Ensure compliance with data security and privacy regulations safeguarding sensitive information and maintaining trust.
• Document and maintain detailed records of data processes and solutions supporting transparency and knowledge retention.
Qualifications:
Required:
• expertise in Spark Optimization
• AWS DevOps
• AWS Glue Studio
• AWS Glue ETL
• AWS Glue Catalog
• Amazon S3
• Apache Spark
• Implement AWS DevOps practices to streamline deployment and operational processes ensuring seamless integration and delivery
• Utilize AWS Glue Studio to design and manage ETL workflows facilitating efficient data transformation and movement
• Leverage AWS Glue ETL to automate data extraction transformation and loading processes improving data accessibility and usability
• Manage AWS Glue Catalog to maintain a comprehensive and organized metadata repository ensuring data consistency and discoverability
• Oversee Amazon S3 storage solutions to ensure secure and scalable data storage enabling efficient data retrieval and management
• Provide technical guidance and support to team members fostering a collaborative and knowledge-sharing environment
• Ensure compliance with data security and privacy regulations safeguarding sensitive information and maintaining trust
• Document and maintain detailed records of data processes and solutions supporting transparency and knowledge retention
• Technical Skills: AWS Data Pipeline creation, AWS Glue Studio, Apache Spark, AWS DevOps, Amazon S3, AWS Glue ETL, AWS Glue Catalog, Pyspark, SQL concepts and Data Modelling concepts
• Functional Skills: Configuration Management, Technology Trends, Root Cause Analysis, Knowledge Management, Requirements Management, Test & Defect Management
• Leadership and Professional development Skills: Execution Excellence, Innovation, Effective Communication, Client Focus, Drive results with accountability, Drive vision and purpose, Build trust, collaboration and transparency, Promote engagement, Drive change and innovation
Company:
Cognizant is a professional services company that helps clients alter their business, operating, and technology models for the digital era. Founded in 1994, the company is headquartered in Teaneck, USA, with a team of 10001+ employees. The company is currently Late Stage.
Cognizant is looking for a Sr. AWS Data Architect who will optimize data processes and contribute to innovative solutions that drive the company's success. The role involves implementing AWS DevOps practices, managing ETL workflows, and ensuring data security and compliance.
Responsibilities:
• Implement AWS DevOps practices to streamline deployment and operational processes ensuring seamless integration and delivery.
• Utilize AWS Glue Studio to design and manage ETL workflows facilitating efficient data transformation and movement.
• Leverage AWS Glue ETL to automate data extraction transformation and loading processes improving data accessibility and usability.
• Manage AWS Glue Catalog to maintain a comprehensive and organized metadata repository ensuring data consistency and discoverability.
• Oversee Amazon S3 storage solutions to ensure secure and scalable data storage enabling efficient data retrieval and management.
• Provide technical guidance and support to team members fostering a collaborative and knowledge-sharing environment.
• Ensure compliance with data security and privacy regulations safeguarding sensitive information and maintaining trust.
• Document and maintain detailed records of data processes and solutions supporting transparency and knowledge retention.
Qualifications:
Required:
• expertise in Spark Optimization
• AWS DevOps
• AWS Glue Studio
• AWS Glue ETL
• AWS Glue Catalog
• Amazon S3
• Apache Spark
• Implement AWS DevOps practices to streamline deployment and operational processes ensuring seamless integration and delivery
• Utilize AWS Glue Studio to design and manage ETL workflows facilitating efficient data transformation and movement
• Leverage AWS Glue ETL to automate data extraction transformation and loading processes improving data accessibility and usability
• Manage AWS Glue Catalog to maintain a comprehensive and organized metadata repository ensuring data consistency and discoverability
• Oversee Amazon S3 storage solutions to ensure secure and scalable data storage enabling efficient data retrieval and management
• Provide technical guidance and support to team members fostering a collaborative and knowledge-sharing environment
• Ensure compliance with data security and privacy regulations safeguarding sensitive information and maintaining trust
• Document and maintain detailed records of data processes and solutions supporting transparency and knowledge retention
• Technical Skills: AWS Data Pipeline creation, AWS Glue Studio, Apache Spark, AWS DevOps, Amazon S3, AWS Glue ETL, AWS Glue Catalog, Pyspark, SQL concepts and Data Modelling concepts
• Functional Skills: Configuration Management, Technology Trends, Root Cause Analysis, Knowledge Management, Requirements Management, Test & Defect Management
• Leadership and Professional development Skills: Execution Excellence, Innovation, Effective Communication, Client Focus, Drive results with accountability, Drive vision and purpose, Build trust, collaboration and transparency, Promote engagement, Drive change and innovation
Company:
Cognizant is a professional services company that helps clients alter their business, operating, and technology models for the digital era. Founded in 1994, the company is headquartered in Teaneck, USA, with a team of 10001+ employees. The company is currently Late Stage.
What Cognizant employees say
Pay
Benefits
Hours and flexibility
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