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Gcs Jobs in Virginia (NOW HIRING)

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

... e.g., GCS, Dataproc) * Demonstrated experience setting up infrastructure for modern data science, machine learning, or Generative AI (e.g., preparing unstructured data, vector databases, RAG ...

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

... e.g., GCS, Dataproc) * Demonstrated experience setting up infrastructure for modern data science, machine learning, or Generative AI (e.g., preparing unstructured data, vector databases, RAG ...

Data Engineer

Reston, VA

$119K - $143K/yr

... e.g., GCS, Dataproc) * Demonstrated experience setting up infrastructure for modern data science, machine learning, or Generative AI (e.g., preparing unstructured data, vector databases, RAG ...

Showing results 41-60

Gcs information

See Virginia salary details

$1.1K

$1.7K

$1.9K

How much do gcs jobs pay per week?

As of Aug 20, 2026, the average weekly pay for gcs in Virginia is $1,655.00, according to ZipRecruiter salary data. Most workers in this role earn between $1,534.62 and $1,782.69 per week, depending on experience, location, and employer.

What is a GCS?

GCS stands for Ground Control Station, which is a system used to control and monitor unmanned vehicles such as drones or UAVs (Unmanned Aerial Vehicles). Operators use GCS to send commands, receive telemetry data, and sometimes view live video feeds from the vehicle. GCS can range from portable laptop-based systems to large, fixed installations. They play a crucial role in ensuring the safe and efficient operation of unmanned systems, often providing interfaces for navigation, mission planning, and system diagnostics.

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

To thrive as a Google Cloud Specialist, you need a solid understanding of cloud computing principles, experience with Google Cloud Platform (GCP) services, and typically a relevant degree or certification such as Google Cloud Professional certifications. Familiarity with tools like Google Kubernetes Engine, BigQuery, and cloud automation systems is common in this role. Strong problem-solving skills, effective communication, and a collaborative mindset help professionals deliver tailored cloud solutions and work efficiently with clients and teams. These skills ensure optimal cloud architecture, smooth project delivery, and alignment with business goals in dynamic technology environments.

What are the primary challenges faced by a Google Cloud Platform (GCP) Cloud Engineer, and how can they be addressed?

As a GCP Cloud Engineer, one of the main challenges is staying updated with rapidly evolving cloud technologies and best practices. You may also encounter complex migration projects, requiring strong problem-solving and collaboration with cross-functional teams such as DevOps, security, and application developers. Proactively engaging in continuous learning, leveraging Google’s official documentation, and participating in cloud community forums can help address these challenges. Additionally, developing strong communication skills is crucial for effectively translating technical requirements and collaborating across diverse teams.

What is the difference between Gcs vs Cloud Engineer?

AspectGcsCloud Engineer
Required CredentialsGoogle Cloud certifications, technical skills in cloud storageCloud certifications (AWS, Azure, Google Cloud), broad cloud knowledge
Work EnvironmentPrimarily cloud storage management, data handlingDesigning, deploying, managing cloud infrastructure
Employer & Industry UsageTech companies, data-driven organizations using Google CloudVarious industries adopting cloud solutions, broader scope

Gcs (Google Cloud Storage Specialist) focuses on managing and optimizing cloud storage solutions within Google Cloud. In contrast, a Cloud Engineer has a broader role, designing and maintaining entire cloud infrastructure across multiple services. While Gcs specialists concentrate on storage, Cloud Engineers handle a wider range of cloud services, making their roles complementary but distinct.

What are popular job titles related to Gcs jobs in Virginia?

For Gcs jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Gcs jobs in Virginia look for?

The top searched job categories for Gcs jobs in Virginia are:

What cities in Virginia are hiring for Gcs jobs?

Cities in Virginia with the most Gcs job openings:

Infographic showing various Gcs job openings in Virginia as of August 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 90% Physical, 4% Hybrid, and 6% Remote job distribution, with an average salary of $86,060 per year, or $41.4 per hour.

Data Engineer

SZNS Solutions LLC

Reston, VA • On-site

$119K - $143K/yr

Full-time

Re-posted 4 days ago


Job description

"SZNS Solutions (pronounced "seasons") is a technology consulting company and Google Cloud Partner based in Reston VA. We specialize in delivering agentic AI and cloud computing solutions. Founded by ex-Googlers with engineers from Google, Amazon, and Capital One, SZNS differentiates itself particularly in AI, data engineering, blockchain, and cloud-native software application development.”

Role Summary

The Data Engineer is the bedrock of intelligence operations, responsible for turning raw, unstructured data into actionable intelligence. You will embed directly with clients to build the data pipelines that power AI workflows. We build systems that don't just move data, but do it with the speed and reliability required for live and automated intelligence. Ultimately, you’ll create the foundations that will influence key strategic decisions for us and our customers.

Key Responsibilities

  • ETL/ELT Pipelines: Architect and deploy pipelines to ingest, transform, and store data from high volume, disparate sources for real-time analysis
  • Build for the Enterprise: Create a highly reliable single source of truth for enterprise intelligence and enablement
  • AI Workflow Enablement: Architect and optimize production-grade data foundations to support high-performance AI workflows and automated decision-making.
  • Operations & Governance: Establish and automate strict data security, quality assurance, and governance processes. Design systems for high fault tolerance and rapid disaster recovery
  • Efficiency: Design and model for efficient queries, resource usage, workload scheduling, and cost

Requirements

Minimum Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
  • 5+ years of experience in data engineering, within a cloud environment, demonstrating a clear progression from engineering into architectural design
  • Proficiency in SQL and strong programming skills in Python, Rust, or Java
  • Experience building and maintaining data pipelines using processing/streaming frameworks (e.g., Kafka, Flink, Beam, Spark) and orchestration tools (e.g., Airflow)
  • Experience architecting data stores and schemas for AI workflows (e.g., RAG)
  • Active Google Cloud certifications, or willingness to obtain within one month of joining
  • Builder mentality and bias for action
  • US Citizen
Preferred Qualifications
  • Deep expertise in the Google Cloud Platform (GCP) ecosystem, specifically building streaming and batch pipelines using Dataflow (Apache Beam), Pub/Sub, BigQuery, and Cloud Composer (Airflow)
  • Strong background in data modeling and architecture across relational (e.g., PostgreSQL), NoSQL (e.g., Firestore, MongoDB), and graph databases (e.g., Neo4j), including modern cloud data warehouses (e.g., BigQuery) and data lakes (e.g., GCS, Dataproc)
  • Demonstrated experience setting up infrastructure for modern data science, machine learning, or Generative AI (e.g., preparing unstructured data, vector databases, RAG pipelines)
  • Familiarity with regulatory compliance frameworks (FedRAMP, HIPAA, etc.) and security strategies
  • Experience with modern data platforms like Snowflake or Databricks

Benefits

  • Competitive salary and benefits package
  • Hybrid work environment (MWF in-person in our Reston office)
  • A collaborative and innovative work environment
  • Continuous learning and development opportunities