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Remote Google Bigquery Jobs in Georgia (NOW HIRING)

Aimpoint Digital

Senior Data Engineer 2026 - US

Atlanta, GA · On-site +1

$101K - $138K/yr

Aimpoint Digital is a dynamic and fully remote data and analytics consultancy. We work alongside ... Experience working with cloud data warehouses (Databricks, Snowflake, Google BigQuery, AWS Redshift ...

Aimpoint Digital

Senior Data Engineer 2026 - US

Atlanta, GA · On-site +1

$101K - $138K/yr

Aimpoint Digital is a dynamic and fully remote data and analytics consultancy. We work alongside ... Experience working with cloud data warehouses (Databricks, Snowflake, Google BigQuery, AWS Redshift ...

The Data Sherpas

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable ... Design and implement data storage solutions using BigQuery, Cloud Storage, and Firestore.

Oscar Health

Associate, Strategic Finance

Atlanta, GA · Remote

$96K - $127K/yr

This is a remote position, open to candidates who reside in: Atlanta, GA. You will be fully remote ... Proficiency in SQL/BigQuery to analyze large datasets * Proficiency working with NetSuite and ...

DoiT

Senior Technical Content Writer

Atlanta, GA · Remote

This remote role is ideally based in the United States, with overlap with US business hours (ET-PT ... An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work alongside ...

Oscar Health

Associate, Strategic Finance

Atlanta, GA · Remote

$96K - $127K/yr

This is a remote position, open to candidates who reside in: Atlanta, GA. You will be fully remote ... Proficiency in SQL/BigQuery to analyze large datasets * Proficiency working with NetSuite and ...

All JobsGoogle Bigquery JobsRemote Google Bigquery JobsRemote Google Bigquery Jobs in Georgia

Remote Google Bigquery information

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 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 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 popular job titles related to Remote Google Bigquery jobs in Georgia?

For Remote Google Bigquery jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Remote Google Bigquery jobs in Georgia look for?

The top searched job categories for Remote Google Bigquery jobs in Georgia are:

Remote Google Bigquery jobs near you
Infographic showing various Remote Google Bigquery job openings in Georgia as of July 2026, with employment types broken down into 6% Locum Tenens, 5% As Needed, 83% Full Time, 1% Part Time, 4% Contract, and 1% Nights. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution.

Senior Data Engineer 2026 - US

Atlanta, GA • On-site, Remote

Aimpoint Digital
51 - 200 employees
Learn more about Aimpoint Digitalexternal

$101K - $138K/yr

Full-time

Re-posted 26 days ago

Job description

Do you enjoy working with clients from different industries to investigate complex business problems and to design end-to-end analytical solutions that will improve their existing processes and ability to derive data-driven insights?
Aimpoint Digital is a dynamic and fully remote data and analytics consultancy. We work alongside the most innovative software providers in the data engineering space to solve our clients' toughest business problems. At Aimpoint Digital, we believe in blending modern tools and techniques with tried-and-true principles to deliver optimal data engineering solutions.
You will:
  • Become a trusted data and AI advisor to our clients, from data owners and analytic users to executive stake holders helping them translate business questions into AI-ready data architectures
  • Work independently as part of a small team to solve complex data engineering use-cases across a variety of industries
  • Design and implement AI-optimized data platforms, including cloud data warehouses, lakehouses, ETL/ELT pipelines, orchestration jobs, and analytic layers that support LLM-driven analytics, natural language querying, and agent-based workflows
  • Build and evolve semantic and analytical layers that power tools like Snowflake Cortex, Databricks Genie, BI platforms, and emerging AI Copilots
  • Use modern platforms and tooling such as Snowflake, Databricks, dbt, Fivetran, and cloud-native orchestration frameworks to deliver scalable solutions, and credentialize your skills with certifications
  • Engineer modern ELT/ETL pipelines that handle structured, semi-structured, and unstructured data to support AI and analytics use cases
  • Design modern data models with an emphasis on metrics layers, knowledge graphs, and semantic consistency for AI consumption
  • Write production-ready code in SQL, Python, and Spark, following software engineering tools and best-practices such as Git and CI/CD
  • Apply AI-assisted data engineering techniques for data exploration, quality checks, schema generation, documentation, lineage, and transformation acceleration
  • Contribute to the evolution of our AI-forward data engineering and infrastructure practice, including internal accelerators, patterns, and client-ready architectures
  • Collaborate with analytics, data science, and ML project teams to productionize AI-enabled analytics, features, and inference pipelines. Note: You will not be developing machine learning models or algorithms

Who you are:
We are building a diverse team of talented and motivated people who deeply understand business problems and enjoy solving them. You are a self-starter who loves working with data to build analytical tools that business users can leverage daily to do their jobs better. You are passionate about contributing to a growing team and establishing best practices.
As a Senior Data Engineer, you will be expected to work independently on client engagements, take part in the development of our practice, aid in business development, and contribute innovative ideas and initiatives to our company.
  • Degree educated in Computer Science, Engineering, Mathematics, or equivalent experience
  • Experienced at partnering with business stakeholders, explaining technical concepts clearly, and shaping solutions around real business outcomes
  • Passionate about modern data engineering and AI trends, including LLM powered analytics, semantic layers, vectorized data access, and metadata-driven architectures
  • Strong written and verbal communication skills required
  • 3+ years working with relational databases and query languages
  • 3+ years building data pipelines in production and ability to work across structured, semi-structured and unstructured data
  • 3+ years data modeling (e.g. star schema, entity-relationship)
  • 3+ years writing clean, maintainable, and robust code in Python, Scala, Java, or similar coding languages
  • 2+ years' experience with dbt Core and/or dbt Cloud preferred
  • Experience enabling or accelerating data platform engineering workflows with AI tools such as Codex, Claude, Copilot, Snowflake Cortex Code, and/or Databricks Genie Code preferred
  • Comfortable working independently on individual workstream, owning end-to-end delivery from design through production
  • Expertise in software engineering concepts and best practices
  • DevOps experience preferred
  • Experience working with cloud data warehouses (Databricks, Snowflake, Google BigQuery, AWS Redshift, Microsoft Synapse) preferred
  • Experience working with cloud ETL/ELT tools (Fivetran, dbt, Matillion, Informatica, Talend, etc.) preferred
  • Experience working with cloud platforms (AWS, Azure, GCP) and container technologies (Docker, Kubernetes) preferred
  • Experience working with Apache Spark preferred
  • Experience preparing data for analytics and following a data science workflow to drive business results preferred
  • Consulting experience strongly preferred
  • Willingness to travel

We are actively seeking candidates for full-time, remote work within the US. Atlanta applicants will have the opportunity to work from headquarters in Sandy Springs, GA.

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