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Remote Data Storage Sales Jobs in Virginia (NOW HIRING)

Hoboken, NJ or Remote with Travel Division : Revenue Department: Customer Success About Us: Quantum ... Collaborate crossfunctionally with Sales, Engineering, Product, Data Science, and Marketing to ...

Description VAST Data is looking for a Sales Director, Data Platform - Federal Civilian to join our ... Strong understanding of database technologies, storage systems, and data management principles.

Senior Engineer

Arlington, VA · On-site +1

$110K - $180K/yr

... data storage * Experience with AWS and/or other cloud computing solutions * Experienced with ... Remote, hybrid, and flexible work options * Team off-site in fun places! * Generous Referral ...

New

Senior Data Engineer

Herndon, VA · On-site +1

$150K - $180K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

This is a full-time, salaried, remote position. Candidate must reside within the Continental U.S ... sales and service revenue. Our team members are driven, creative, and collaborative, enjoying a ...

Senior Data Engineer

Herndon, VA · Remote

$150K - $180K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

This is a full-time, salaried, remote position. Candidate must reside within the Continental U.S ... sales and service revenue. Our team members are driven, creative, and collaborative, enjoying a ...

Showing results 41-60

Remote Data Storage Sales information

What is the difference between Remote Data Storage Sales vs Remote Cloud Solutions Sales?

AspectRemote Data Storage SalesRemote Cloud Solutions Sales
CredentialsSales certifications, technical knowledge of storage productsSales certifications, understanding of cloud platforms and services
Work EnvironmentRemote, client-facing, technical sales rolesRemote, client-facing, consultative sales roles
Industry UsageData storage providers, hardware/software vendorsCloud service providers, SaaS companies
Search & Comparison IntentUnderstanding roles in data storage sales, career optionsComparing cloud sales roles, career growth in cloud solutions

Remote Data Storage Sales and Remote Cloud Solutions Sales share similarities in sales approach and technical knowledge but focus on different products. Data storage sales emphasize physical or software storage solutions, while cloud solutions sales focus on cloud-based services. Both roles require technical understanding and client interaction, but their target markets and product knowledge differ.

What are the key skills and qualifications needed to thrive as a remote data storage sales professional?

To excel in Remote Data Storage Sales, you need a solid understanding of cloud storage solutions, data management principles, and proven sales experience, often supported by a relevant degree or technical certifications. Familiarity with CRM platforms, cloud storage providers (like AWS, Azure, or Google Cloud), and sales enablement tools is typically required. Strong communication, relationship-building, and self-motivation are valuable soft skills for engaging clients and closing deals remotely. These skills ensure you can effectively understand client needs, present tailored solutions, and drive sales results in a competitive, technology-driven market.

What are some common challenges faced by remote data storage sales professionals, and how can they be addressed?

Remote Data Storage Sales professionals often face challenges such as building trust with clients remotely, staying current with rapidly evolving technology, and differentiating their solutions in a crowded marketplace. Success often depends on proactive communication, leveraging virtual demos, and maintaining strong product knowledge. Regular collaboration with technical teams and ongoing training can help address client concerns and demonstrate expertise, ultimately leading to stronger client relationships and sales outcomes.

What is a remote data storage sales professional?

A Remote Data Storage Sales job involves selling cloud-based or off-site data storage solutions to businesses or individuals. Professionals in this role connect with potential clients, understand their data storage needs, and recommend appropriate products or services. They often work remotely, using digital communication tools to manage sales pipelines and close deals. Their goal is to help clients securely store, access, and manage their data while meeting sales targets and building lasting relationships.
What cities in Virginia are hiring for Remote Data Storage Sales jobs? Cities in Virginia with the most Remote Data Storage Sales job openings:

Software Engineer (Full Stack) - SME

GRVTY

Springfield, VA • Remote

Full-time

Re-posted 19 days ago


Job description

What Impact You'll Have:

Join a mission-focused team where your work directly supports critical national security objectives. We are seeking a Subject Matter Expert (SME) Full Stack Developer to lead the design, development, and delivery of scalable, mission-driven applications within an ML/Ops environment. This role combines deep technical expertise with advanced system-level thinking and close collaboration across engineering, data science, and customer stakeholder teams.

The Full Stack Developer will perform rapid application design, ETL, data analysis, and interpretation while developing rules and methodologies for data collection and analysis. You will architect, develop, and maintain a Python-based data warehouse processing system that serves as the backend for a user-facing application, while also leading development of modern GUI applications using REST APIs and contemporary web frameworks.

You will work closely with data scientists, computer vision engineers, ETL engineers, and intelligence analysts to integrate machine learning capabilities into production systems, enabling scalable model deployment, monitoring, and continuous improvement. This role emphasizes ownership, technical leadership, and delivery of production-ready solutions that operate reliably in dynamic, real-world environments.

What You'll Be Owning:

Lead and participate in the architectural design of complex features early in the development lifecycle.
Translate customer requirements and roadmap priorities into technical solutions, tasks, timelines, and resource plans.
Develop, integrate, and maintain full stack applications supporting ML/Ops pipelines and data-driven systems.
Design and implement scalable APIs and services to support machine learning model deployment and inference.
Develop and maintain data pipelines, ETL processes, and data storage solutions for large-scale datasets.
Collaborate with data scientists and ML engineers to operationalize models within production environments.
Optimize application and system performance for scalability, reliability, and efficiency, including edge and distributed environments when applicable.
Conduct peer reviews and establish coding standards to improve overall code quality and maintainability.
Guide development testing, exploratory testing, automated testing, and validation strategies.
Own code in production environments, respond to incidents, and lead root cause analysis and continuous improvement efforts.
Ensure security, compliance, and governance are maintained throughout the development lifecycle.
Perform technical planning, system integration, verification and validation, and risk assessments across system components.
Mentor and develop junior and mid-level engineers, fostering technical growth and high-performing teams.
Drive adoption of modern ML/Ops practices, tools, and automation frameworks across the team.

What You Must Have:

Active TS/SCI clearance with the ability to obtain a CI poly
Bachelor's degree in Computer Science, Engineering, or a related technical field.
14+ years of professional experience in full stack software development.
Expert-level proficiency in Python and object-oriented design patterns.
Extensive experience developing backend systems, APIs, and data processing pipelines.
Strong experience with modern web development frameworks, including React.js, Node.js, and/or Electron.
Deep understanding of data modeling techniques and experience working with large-scale and time series datasets.
Experience with relational and non-relational databases such as PostgreSQL, MongoDB, and BigQuery.
Experience building and maintaining RESTful APIs and microservices architectures.
Experience supporting machine learning workflows, including model integration, deployment, and monitoring.
Familiarity with ML/Ops tools and utilities such as MLflow, DVC, and/or Optuna.
Strong experience with Python libraries such as NumPy and Pandas.
Experience with Python web frameworks such as Flask, FastAPI, Pydantic, Gunicorn, and Uvicorn.
Experience with containerization and DevOps practices, including Docker and CI/CD pipelines.
Experience with web servers such as Apache and Nginx.
Experience working within Agile development environments and using associated tools.

What Would be Nice to Have:

Experience supporting government or defense-related programs.
Experience integrating computer vision or machine learning capabilities into operational systems.
Knowledge of real-time data processing, streaming architectures, or distributed systems.
Experience with cloud-based ML/Ops environments and infrastructure (AWS, Azure, or Google Cloud Platform).
Experience with parallelization and multiprocessing frameworks such as Dask.
Knowledge of geospatial data processing tools and libraries including GeoPandas, Shapely, Rasterio, QGIS, and ArcPy.
Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
Experience with remote procedure call technologies such as gRPC and JSON-RPC.

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