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Data Optimizer Non Technical Jobs (NOW HIRING)

Staffed4U

Data Engineer

Chantilly, VA · On-site

$118K - $142K/yr

Communicate technical concepts effectively to both technical and non-technical stakeholders ... Experience modeling, querying, and optimizing Neo4j databases. * Experience supporting advanced ...

New

Staffed4U

Data Engineer

Chantilly, VA

$118K - $142K/yr

Communicate technical concepts effectively to both technical and non-technical stakeholders ... Experience modeling, querying, and optimizing Neo4j databases. * Experience supporting advanced ...

New

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

You'll also harness mathematical optimization to identify the most profitable business strategies ... Success in this position requires strong collaboration with both technical and non-technical teams ...

United States Cold Storage

Data Scientist II

Camden, NJ · On-site

$100K - $120K/yr

... non-technical stakeholders • Applied data science use cases including network and route optimization, warehouse optimization, demand and capacity forecasting, anomaly detection, and customer ...

USCS

Data Scientist II

Camden, NJ · On-site

$100K - $120K/yr

... non-technical stakeholders • Applied data science use cases including network and route optimization, warehouse optimization, demand and capacity forecasting, anomaly detection, and customer ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

You'll also harness mathematical optimization to identify the most profitable business strategies ... Success in this position requires strong collaboration with both technical and non-technical teams ...

Stagecoach East

Sr. Data Scientist

Washington, DC · Hybrid

Developing and optimizing machine learning models and algorithms using scikit-learn, xgboost ... Communication with non-technical audiences and ability to develop and drive a presentation.

Visa

Sr. Data Scientist

Washington, DC · Hybrid

Developing and optimizing machine learning models and algorithms using scikit-learn, xgboost ... Communication with non-technical audiences and ability to develop and drive a presentation.

Visa

Sr. Data Scientist

Washington, DC · On-site

Developing and optimizing machine learning models and algorithms using scikit-learn, xgboost ... Communication with non-technical audiences and ability to develop and drive a presentation.

iSpace, Inc

Senior Data Analyst

Los Angeles, CA · Hybrid

$92K - $116K/yr

Conduct the application of advanced statistical methods to identify the most optimal KPIs for each ... Create presentations with the ability to communicate insights to both technical and non-technical ...

AHU Technologies, Inc.

Data Analyst

Washington, DC · On-site

$61 - $68/hr

... Objects Management & optimization, and agency data dashboard configuration, development and ... a non-technical audience • Create public-facing written reports to present analytic findings to ...

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All JobsData Optimizer Non Technical Jobs

Data Optimizer Non Technical information

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$52

$73

How much do data optimizer non technical jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for data optimizer non technical in the United States is $52.10, according to ZipRecruiter salary data. Most workers in this role earn between $45.91 and $58.89 per hour, depending on experience, location, and employer.

How does a Data Optimizer (Non-Technical) typically collaborate with other departments to ensure data quality and usability?

A Data Optimizer (Non-Technical) often acts as a liaison between data users and technical teams, working closely with departments like marketing, sales, and operations to understand their data needs and challenges. They facilitate communication, gather requirements, and help interpret data outputs to ensure information is accurate, accessible, and actionable for stakeholders. Collaboration may include organizing meetings, documenting processes, and providing feedback to data engineers or analysts to improve data systems. This cross-functional role is crucial for ensuring that data-driven decisions are based on reliable and well-structured information.

What is a Data Optimizer (Non-Technical)?

A Data Optimizer (Non-Technical) is a professional who focuses on improving how data is organized, managed, and utilized within a company, without needing advanced technical skills like programming. Their role often involves evaluating data processes, ensuring data quality, and recommending improvements for better decision-making. They may also coordinate with technical teams, create reports, and help implement best practices for data handling. This position is ideal for individuals with strong analytical, organizational, and communication skills who want to work with data in a more strategic or administrative capacity.

What are the key skills and qualifications needed to thrive as a Data Optimizer (Non-Technical), and why are they important?

To thrive as a Data Optimizer (Non-Technical), strong analytical thinking, attention to detail, and a foundational understanding of data management principles are essential, typically supported by a bachelor’s degree in business, analytics, or a related field. Familiarity with data visualization tools, spreadsheet software like Excel, and basic reporting platforms is commonly required. Excellent communication, problem-solving ability, and collaboration skills help individuals effectively interpret data trends and work with diverse teams. These skills enable accurate data-driven decision-making and ensure data processes align with business goals.

What is the difference between Data Optimizer Non Technical vs Data Analyst?

AspectData Optimizer Non TechnicalData Analyst
Required CredentialsCertifications in data tools, basic analytics, or data managementDegree in statistics, mathematics, or related field; often certifications in data analysis tools
Work EnvironmentCollaborates with technical teams, focuses on data quality and process improvementAnalyzes data sets, creates reports, and provides insights to stakeholders
Employer & Industry UsageUsed across industries for data quality and process optimization rolesCommonly employed in finance, marketing, healthcare, and tech sectors for data-driven decision making

In summary, Data Optimizer Non Technical focuses on improving data quality and processes without deep technical analysis, while Data Analyst involves analyzing data sets to generate insights. Both roles require data-related certifications but differ in their core responsibilities and work environment.

Data Engineer

Staffed4U

Chantilly, VA • On-site

$118K - $142K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

Job description

Data Engineer

Location: Chantilly, VA
Work Schedule: Full-Time, Onsite
Clearance Required: Active TS/SCI with Full Scope Polygraph (FSP)
Employment Type: W-2

Position Overview

We are seeking a talented and mission-focused Data Engineer to join our growing team supporting cutting-edge intelligence community initiatives in Chantilly, VA. This role offers the opportunity to work with large-scale datasets and contribute to the development of a custom enterprise platform supporting critical mission objectives.

The selected candidate will play a key role in designing, building, and optimizing scalable data pipelines and architectures that support analytics, machine learning, and enterprise data integration efforts. This position is funded for an initial 9-12 month period aligned with defined mission deliverables and system development timelines, with all development performed onsite at the customer location.

Key ResponsibilitiesData Engineering & Pipeline Development
  • Design, develop, and maintain ETL/ELT pipelines for both batch and real-time data processing using Python and SQL.
  • Integrate data from a variety of structured and unstructured sources, including databases, APIs, streaming platforms, PDFs, and Microsoft Office files.
  • Build scalable and maintainable data architectures to support analytics and machine learning workloads.
  • Optimize data processing workflows and queries for performance, scalability, and cost efficiency within AWS environments.
  • Support future pipeline scalability through exposure to PySpark and other distributed data processing frameworks.
  • Develop and maintain web scraping and data ingestion workflows to collect and process open-source data.
  • Transform collected information into structured datasets and visualizations for stakeholder analysis and decision-making.
Data Management & Optimization
  • Collect, clean, validate, and manage large volumes of structured and unstructured data.
  • Implement data quality controls, validation procedures, and version management practices.
  • Design and optimize data storage solutions utilizing AWS S3 for raw, intermediate, and production datasets.
  • Implement data governance best practices including documentation, cataloging, lineage tracking, and security controls.
  • Ensure compliance with customer and security requirements for data management and handling.
Collaboration & Machine Learning Support
  • Partner closely with Data Scientists, Analysts, and Engineering teams to understand business and mission requirements.
  • Prepare clean, structured, and feature-ready datasets for analytics and machine learning applications.
  • Support feature engineering, aggregation, and large-scale data transformations.
  • Assist with deploying machine learning models into production environments while supporting monitoring, versioning, and performance optimization.
  • Integrate and consume REST APIs to support data acquisition and application workflows.
  • Utilize Docker, Kubernetes, Git, and CI/CD pipelines to support deployment and operational workflows.
Documentation & Communication
  • Document data pipelines, architectures, schemas, and transformation processes.
  • Communicate technical concepts effectively to both technical and non-technical stakeholders.
  • Participate in code reviews and promote engineering best practices across the team.
  • Contribute to continuous improvement efforts related to data engineering, automation, and platform development.
Required QualificationsExperience
  • 3-5+ years of professional experience in Data Engineering or a related technical field.
  • Experience designing and implementing ETL/ELT pipelines.
  • Experience processing and managing large-scale structured and unstructured datasets.
  • Experience working in cloud-based data environments.
Technical Skills
  • Strong proficiency with Python and SQL.
  • Experience with PySpark or other distributed processing frameworks (highly desired).
  • Experience with ElasticSearch/OpenSearch technologies.
  • Experience working within AWS cloud environments.
  • Experience supporting Linux-based systems.
  • Proficiency with Git for version control and collaborative development.
  • Understanding of machine learning workflows and MLOps concepts.
  • Experience integrating and consuming REST APIs.
  • Familiarity with Docker, Kubernetes, and CI/CD pipelines.
Clearance Requirements
  • Active TS/SCI with Full Scope Polygraph (FSP) is required.
  • U.S. Citizenship required.
Professional Skills
  • Strong collaboration and communication skills.
  • Ability to communicate complex technical concepts to non-technical audiences.
  • Detail-oriented with a strong commitment to data quality and integrity.
  • Ability to manage multiple priorities in a fast-paced mission environment.
  • Strong analytical and problem-solving capabilities.
Desired Qualifications
  • Hands-on experience with graph databases.
  • Experience modeling, querying, and optimizing Neo4j databases.
  • Experience supporting advanced analytics, knowledge graphs, or entity resolution systems.
  • Experience working within Intelligence Community environments.
Why Join Us?

This is an opportunity to work alongside highly skilled engineers, analysts, and data scientists supporting critical national security missions. You'll have the chance to build scalable data solutions, support advanced analytics initiatives, and help shape the future of enterprise data systems in a dynamic and impactful environment.

Benefits
  • Competitive Compensation
  • Comprehensive Medical, Dental, and Vision Coverage
  • 401(k) with Company Contribution
  • Paid Time Off and Company Holidays
  • Life and Disability Insurance
  • Professional Development Opportunities
  • Challenging and Meaningful Mission-Focused Work
  • Long-Term Career Growth Opportunities
Equal Opportunity Employer

We are committed to fostering an inclusive workplace and welcome qualified applicants from all backgrounds. Employment decisions are made without regard to race, color, religion, sex, national origin, disability, veteran status, or any other protected characteristic.

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