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Remote Seismic Data Processing Geophysicist Jobs in Dallas, TX

We are currently recruiting for a Data Specialist to join our organization; this is a remote ... Experience using AIbased document extraction tools and data processing technologies. * Familiarity ...

... and processes * Outstanding analytical and problem-solving skills partnered with storytelling ... Data science experience * Retail experience * SQL Coding, Microsoft Access, Macro building ...

Program Manager

Plano, TX ยท On-site +1

Extensive experience in health care data processing (claims and admin) (Required) * Strong ... Remote position.

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Remote Seismic Data Processing Geophysicist information

See Dallas, TX salary details

$48K

$94.4K

$142.4K

How much do remote seismic data processing geophysicist jobs pay per year?

As of Aug 19, 2026, the average yearly pay for remote seismic data processing geophysicist in Dallas, TX is $94,384.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,200.00 and $110,800.00 per year, depending on experience, location, and employer.

What does a remote seismic data processing geophysicist do?

A Remote Seismic Data Processing Geophysicist specializes in analyzing seismic data, often from a remote location, to help interpret subsurface geological structures. They use advanced software and algorithms to process raw seismic signals collected during surveys, improving the quality and clarity of the data. Their work is crucial in industries such as oil and gas exploration, environmental studies, and earthquake research. By working remotely, they leverage digital tools to collaborate with teams and deliver results without being on-site.

What are the key skills and qualifications needed to thrive as a remote seismic data processing geophysicist?

To thrive as a Remote Seismic Data Processing Geophysicist, you need a strong background in geophysics, seismic interpretation, and quantitative analysis, usually supported by a relevant degree such as geophysics, geology, or physics. Proficiency with seismic processing software (e.g., ProMAX, Petrel, or SeisSpace), programming languages (such as Python or MATLAB), and experience with remote collaboration tools are typically required. Strong analytical thinking, attention to detail, and effective communication skills help professionals excel in interpreting complex datasets and reporting findings to multidisciplinary teams. These skills ensure accurate seismic data analysis, efficient remote collaboration, and effective contribution to exploration or monitoring projects.

What are some common challenges faced by remote seismic data processing geophysicists, and how can they be managed?

Remote Seismic Data Processing Geophysicists often encounter challenges such as managing large data sets, ensuring data quality, and troubleshooting processing software issues without on-site support. Effective communication with field teams and clients is crucial to clarify data requirements and resolve discrepancies quickly. Staying updated with the latest processing techniques and maintaining strong organizational skills help manage project deadlines and deliver accurate results. Collaboration tools and regular virtual meetings are commonly used to facilitate teamwork and overcome the limitations of remote work.

What are the most commonly searched types of Seismic Data Processing Geophysicist jobs in Dallas, TX?

The most popular types of Seismic Data Processing Geophysicist jobs in Dallas, TX are:

What are popular job titles related to Remote Seismic Data Processing Geophysicist jobs in Dallas, TX?

For Remote Seismic Data Processing Geophysicist jobs in Dallas, TX, the most frequently searched job titles are:

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The top searched job categories for Remote Seismic Data Processing Geophysicist jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Remote Seismic Data Processing Geophysicist jobs?

Cities near Dallas, TX with the most Remote Seismic Data Processing Geophysicist job openings:

Google Cloud Data Migration Lead

IT America Inc

Dallas, TX โ€ข Remote

Contractor

Re-posted 15 days ago


Job description

Position: Google Cloud Data Migration – Data Migration Team Lead

Location: Remote

Duration: Long term contract

Job Summary:

Seeking a Google Cloud data engineer to design, build, and maintain scalable and efficient data processing systems on the Google Cloud platform. This engineer will be responsible for the entire data lifecycle, from ingestion and storage to processing, transformation, and analysis. Their work will enable client organizations to make data-driven decisions by providing clean, high-quality data to business intelligence tools, AI systems, analysts and data scientists.

Key Responsibilities:

  • Serve as Data Migration team leader for a large data and application migration to the Google Cloud platform.
  • As Data Migration team leader, this individual will be responsible for our team’s endto-end data architecture and migration planning to support the migration effort as well as future-state client efforts on the Google Cloud platform.
  • As Data Migration team leader, this individual will collaborate closely with the overall Google Cloud migration team leadership, working to deliver a successful application and data migration.
  • Design and build data pipelines: Develop and maintain reliable and scalable batch and real-time data pipelines using GCP tools such as Cloud Dataflow (based on Apache Beam), Cloud Pub/Sub, and Cloud Composer (for Apache Airflow).
  • Create and manage data storage solutions: Implement data warehousing and data lake solutions using GCP products like BigQuery, Cloud Storage, and other transactional or NoSQL databases such as CloudSQL or Bigtable.
  • Ensure data quality and integrity: Develop and enforce procedures for data governance, quality control, and validation throughout the data pipeline to ensure data is accurate and reliable.
  • Optimize performance and cost: Monitor data infrastructure and pipelines to identify and resolve performance bottlenecks, ensuring that all data solutions are cost-effective and scalable.
  • Collaborate with other teams: Work closely with data scientists, analysts, and business stakeholders to gather requirements and understand data needs, translating them into technical specifications.
  • Automate and orchestrate workflows: Automate data processes and manage complex workflows using tools like Cloud Composer.
  • Implement security: Design and enforce data security and access controls using GCP Identity and Access Management (IAM) and other best practices.
  • Maintain documentation: Create and maintain clear documentation for data pipelines, architecture, and operational procedures.

Required Skills & Qualifications:

  • GCP Certified professional
  • 8+ years of data engineering experience developing large data pipelines in very complex environments
  • Very Strong SQL skills and ability to build very complex transformation data pipelines using custom ETL framework in Google BigQuery environment
  • Very strong understanding of data migration methods and tooling, with hands-on experience in at least three (3) data migrations to Google Cloud

Google Cloud Platform: Hands-on experience with key GCP data services is essential, including:

  1. BigQuery: For data warehousing and analytics.
  2. Cloud Dataflow: For building and managing data pipelines.
  3. Cloud Storage: For storing large volumes of data.
  4. Cloud Composer: For orchestrating workflows.
  5. Cloud Pub/Sub: For real-time messaging and event ingestion.
  6. DataProc: For running Apache Spark and other open-source frameworks.
  • Programming languages: Strong proficiency in programming languages, most commonly Python, is mandatory. Experience with Java or Scala is also preferred.
  • SQL expertise: Advanced SQL skills for data analysis, transformation, and optimization within BigQuery and other databases.
  • ETL/ELT: Deep knowledge of Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes.
  • Infrastructure as Code (IaC): Experience with tools like Terraform for deploying and managing cloud infrastructure.
  • CI/CD: Familiarity with continuous integration and continuous deployment (CI/CD) pipelines using tools such as GitHub Actions or Jenkins.
  • Data modeling: Understanding of data modeling, data warehousing, and data lake concepts