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Remote Google Bigquery Jobs in Virginia (NOW HIRING)

Software Engineer-AFRL

Alexandria, VA ยท On-site +1

$131K - $172K/yr

Remote / Alexandria, VA Clearance: Active TS/SCI or eligibility to be cleared Are you ready to be ... Experience with Big Data processing tools, such as Spark/Hadoop, Google's BigQuery, AWS's Athena ...

Traffic Intelligence Specialist

Herndon, VA ยท Remote

$90K - $110K/yr

This is a full-time, salaried, remote position. Employee must be located within the Continental U.S ... Google Analytics 4 (GA4) * Google Tag Manager (GTM) and Server-Side GTM * Understanding of CDN ...

Traffic Intelligence Specialist

Herndon, VA ยท On-site +1

$90K - $110K/yr

This is a full-time, salaried, remote position. Employee must be located within the Continental U.S ... Google Analytics 4 (GA4) * Google Tag Manager (GTM) and Server-Side GTM * Understanding of CDN ...

Remote / Alexandria, VA Clearance: Active TS/SCI or eligibility to be cleared GeoDelphi, Inc. dba ... Experience with AWS, Azure, or Google Cloud. * Experience building geospatial web applications and ...

Remote Google Bigquery information

What are some common challenges faced by professionals working remotely with Google BigQuery, and how can they be addressed?

One common challenge remote Google BigQuery professionals face is optimizing query performance while managing cost, since inefficient queries can quickly increase expenses. Collaboration with distributed teams can also be tricky, especially when aligning on data schema changes or troubleshooting issues across time zones. To address these, it's helpful to establish clear documentation practices, use version control for SQL scripts, and schedule regular check-ins with team members. Leveraging Google BigQuery's built-in monitoring and cost control tools also helps maintain project efficiency and budget constraints.

What is the difference between Remote Google Bigquery vs Remote Data Analyst?

AspectRemote Google BigqueryRemote Data Analyst
Required CredentialsSQL, Cloud certifications, Google Cloud certificationsSQL, Data analysis, Excel, sometimes certifications
Work EnvironmentCloud platforms, data warehouses, remote teamsData visualization tools, spreadsheets, reporting platforms
Industry UsageData engineering, cloud services, analyticsBusiness intelligence, reporting, insights

Remote Google Bigquery specialists focus on managing and querying large datasets using Google Cloud, requiring technical skills and cloud certifications. Remote Data Analysts interpret data, create reports, and provide insights, often using visualization tools. While both roles work remotely and handle data, Bigquery roles are more technical and cloud-focused, whereas Data Analysts focus on analysis and reporting.

What are the key skills and qualifications needed to thrive as a remote Google BigQuery specialist?

To excel as a Remote Google BigQuery Specialist, you need a solid background in SQL, data warehousing concepts, and experience with cloud-based analytics platforms, typically supported by a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP), BigQuery ML, data visualization tools like Looker or Tableau, and relevant certifications such as Google Professional Data Engineer are highly beneficial. Strong problem-solving skills, attention to detail, and effective remote communication set top performers apart. These skills and qualifications enable efficient management of large datasets, insightful analytics, and seamless collaboration in distributed teams.

What is a remote Google BigQuery?

A Remote Google BigQuery job is a position where professionals manage, analyze, and optimize large datasets using Google BigQuery, a fully-managed cloud data warehouse, while working from a location outside of a traditional office. These roles typically involve writing SQL queries, building data pipelines, and collaborating with data engineers and analysts to derive insights from data stored in the cloud. Remote BigQuery specialists may also be responsible for maintaining data security, optimizing query performance, and integrating BigQuery with other data tools. This flexible setup allows employees to work from anywhere with a stable internet connection while supporting organizations' data needs.
What are popular job titles related to Remote Google Bigquery jobs in Virginia? For Remote Google Bigquery jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Google Bigquery jobs in Virginia look for? The top searched job categories for Remote Google Bigquery jobs in Virginia are:
What cities in Virginia are hiring for Remote Google Bigquery jobs? Cities in Virginia with the most Remote Google Bigquery job openings:

$64.25 - $85.75/hr

Full-time

Dental, Vision, Life, Retirement

Re-posted 2 days ago


Job description

Strategic Innovation Group (SIG) is seeking a Cloud/AI Engineer to design, develop, and deploy secure, scalable cloud-native and artificial intelligence solutions supporting Federal Aviation Administration (FAA) programs. This role serves as a senior technical leader responsible for modernizing legacy systems, architecting enterprise cloud platforms, developing production-grade AI applications, and implementing Generative AI capabilities including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI solutions. The successful candidate will collaborate closely with government stakeholders, product teams, and engineering staff to deliver innovative, mission-critical technologies that improve operational efficiency, enable data-driven decision-making, and advance the FAA's digital transformation initiatives while meeting stringent security, compliance, and governance requirements.

SIG is a fast growing 8(a) government contractor based in Arlington, Virginia. We offer a broad range of technical expertise and experience in Digital Transformation, Data Management/Data Science, and Systems Modernization. At SIG, our people are our mission. Come join our team! A successful candidate will be offered the following:

Greatwork/life balance
Eligibilityforperformance-basedparticipationincashbonuses
Potential toparticipatein growth of the company through incentives
Excellent benefits,includinghealth, dental, vision,generousPTO, a 401(k) with match, life insurance, short- and long-term disability,anda health savings account (HSA)
Additionally, this position is expected to be generally remote, with occasional visits to the office and client facilities in the Washington, DC metropolitan area as needed.

ESSENTIAL DUTIES AND RESPONSIBILITIES

The essential functions include, but are not limited to the following:

  • Lead the design, development, deployment, and sustainment of secure, scalable cloud and AI solutions supporting FAA mission objectives.
  • Collaborate with government stakeholders to translate business requirements into innovative, mission-focused technology solutions.
  • Lead the modernization of legacy systems and enterprise platforms through cloud transformation and application modernization initiatives.
  • Establish and promote architecture, engineering, security, and software development best practices across project teams.
  • Provide technical leadership, mentoring, and guidance to engineering teams while supporting Agile project delivery.
  • Ensure solutions meet federal security, governance, compliance, and operational requirements throughout the system lifecycle.
  • Develop and maintain technical documentation, architecture artifacts, and implementation plans to support operations and compliance.
  • Evaluate emerging technologies, resolve complex technical challenges, and recommend improvements that enhance performance, reliability, and mission outcomes.
  • Perform other duties as assigned.

REQUIRED EXPERIENCE/QUALIFICATIONS

  • Bachelor's degree in Computer Science, Engineering, or a related technical field.
  • Cloud Engineer experience: 20+ years
  • AI Engineer experience: 3+ years
  • Experience delivering enterprise-scale technology solutions across public-sector and private-sector organizations, including highly ambiguous environments requiring problem discovery, requirements definition, and solution development.
  • Hands-on experience in cloud engineering, cloud-based application development, and full stack software engineering.
  • Proven track record designing, building, deploying, and operating production-grade applications spanning front-end interfaces, backend services, and cloud data platforms.
  • Experience migrating legacy on-premises systems to the cloud and refactoring monolithic legacy codebases into microservices architectures and cloud-native tooling, using Docker, Kubernetes, serverless services, and cloud platforms such as AWS, Azure, or Google Cloud.
  • Experience leading or executing migrations from on-premises data warehouses to cloud-based data warehouse platforms (e.g., Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse), including data pipeline redesign, schema conversion, and validation of data integrity throughout the migration.
  • Strong proficiency in Python, JavaScript/TypeScript, React, FastAPI, SQL, Spark/PySpark, REST APIs, and modern software development frameworks.
  • Expertise implementing CI/CD pipelines, DevOps practices, infrastructure automation (e.g., Terraform, CloudFormation), and platform engineering principles to support scalable cloud delivery.
  • Experience integrating enterprise systems through APIs, event-driven architectures, workflow orchestration platforms, and distributed services.
    Strong understanding of software engineering fundamentals, distributed systems, cloud architecture, and cloud application engineering best practices.
  • Demonstrated ability to architect secure, scalable, and resilient cloud systems with attention to governance, auditability, data protection, and access controls.
  • Hands-on experience developing and deploying Generative AI solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI systems, semantic search, and vector databases, integrated into cloud-native application architectures.
  • Experience managing the AI application lifecycle within cloud environments, including data ingestion, model integration, deployment, monitoring, observability, and continuous improvement using cloud-native MLOps tooling.
  • Proven ability to collaborate with business stakeholders, product teams, and technical leadership to translate business requirements into scalable technical solutions and AI-enabled products.
  • Experience delivering mission-critical applications in regulated, compliance-sensitive, or enterprise environments.
  • Strong analytical, problem-solving, and systems-thinking skills with the ability to identify operational challenges and develop technology solutions that deliver measurable business value.


PREFERRED EXPERIENCE/QUALIFICATIONS

  • Prior experience in federal contracting or highly regulated enterprise environments.
  • Active FAA clearance


SPECIAL REQUIREMENTS/SECURITY CLEARANCE

Must have ability to obtain a Public Trust clearance