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Remote Seismic Data Processing Jobs in Missouri (NOW HIRING)

Data Engineer

Chesterfield, MO ยท On-site +1

$113K - $136K/yr

Description Data Engineer Chesterfield Office Hybrid or Remote Why You'll Want to Join! Join a ... We leverage cutting-edge technology to streamline financial and operational processes, improving ...

Data Engineer

Chesterfield, MO ยท On-site +1

$113K - $136K/yr

Job Type Full-time Description Data Engineer Chesterfield Office Hybrid or Remote Why You'll Want ... We leverage cutting-edge technology to streamline financial and operational processes, improving ...

Data Engineer - Multiple Positions

Chesterfield, MO ยท Remote

$113K - $136K/yr

United States - Remote Employment Type: Full-Time and Contract Data Engineer Description: As a Data ... tools for data processing and analysis. You will play a pivotal role in managing data ...

$88K - $106K/yr

Build and optimize large-scale data processing pipelines using Python, PySpark, Spark, and ... Fully remote work environment offering flexibility and work-life balance. * Personalized career ...

... processes, climate systems, and natural resources. Ability to explain the rock cycle, weather ... seismic data, and understanding watershed dynamics. Emphasizes observational skills and evidence ...

... processes, climate systems, and natural resources. Ability to explain the rock cycle, weather ... seismic data, and understanding watershed dynamics. Emphasizes observational skills and evidence ...

... processes, climate systems, and natural resources. Ability to explain the rock cycle, weather ... seismic data, and understanding watershed dynamics. Emphasizes observational skills and evidence ...

$88K - $106K/yr

Working in a fully remote, international environment, you'll collaborate closely with data ... Familiarity with distributed systems or large-scale data processing tools. * Understanding of data ...

$88K - $106K/yr

We are currently looking for a Data Engineer (DBT, Snowflake & SQL) in Netherlands. This is an ... processes, and collaborative development practices is highly desirable. Benefits: * Fully remote ...

... fully remote and agile environment. This is an ideal opportunity for professionals passionate about Generative AI, information retrieval, and high-performance data processing who want to make a ...

Fri remote) for candidates in the Kansas City area and open to qualified remote candidates outside ... Designed and implemented frameworks, processes, and metrics for a data office/function within ...

$40K - $110K/yr

We are currently looking for a Full-Stack Geospatial Data Engineer in Netherlands. This is an ... remote sensing workflows, GIS tools, and satellite imagery processing. * Experience with cloud ...

$49.25 - $63.25/hr

Create and maintain technical documentation, process flows, and best practice guidelines ... Benefits: * Competitive compensation package. * Flexible remote working arrangement.

Senior AI Engineer

Chesterfield, MO ยท Remote

$54.75 - $70.50/hr

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States - Remote Employment Type ... Processing (NLP) models, for our diverse client base.Key Responsibilities Serve as a primary ...

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Remote Seismic Data Processing information

What are some common challenges faced by professionals in remote seismic data processing roles, and how can they be addressed?

One common challenge in remote seismic data processing is ensuring reliable data transfer and storage, as large volumes of seismic data must be securely transmitted and accessed remotely. Additionally, collaborating effectively with geophysicists and field teams can be more difficult without in-person interaction, so strong communication skills and familiarity with collaborative platforms are essential. Addressing these challenges involves establishing robust IT infrastructure, utilizing secure cloud services, and maintaining regular virtual meetings to ensure alignment and data integrity throughout the project lifecycle.

What is remote seismic data processing?

Remote seismic data processing is the analysis and interpretation of seismic data from a distance, often using cloud-based or remote-access software. This process involves collecting raw seismic signals, processing the data to remove noise, and generating subsurface images for applications such as oil and gas exploration or earthquake monitoring. Remote processing allows geophysicists and analysts to work from anywhere, increasing efficiency and collaboration across locations. It also enables companies to quickly scale resources and access specialized expertise without being onsite.

What are the key skills and qualifications needed to thrive as a Remote Seismic Data Processing Specialist, and why are they important?

To excel in Remote Seismic Data Processing, you need a solid background in geophysics or a related field, with expertise in seismic data analysis and interpretation. Familiarity with specialized seismic processing software (such as ProMAX or SeisSpace), programming languages like Python or MATLAB, and sometimes relevant certifications, is often required. Strong problem-solving skills, attention to detail, and effective collaboration and communication abilities set top performers apart. These competencies ensure accurate data interpretation and effective teamwork, which are crucial for delivering reliable results in energy exploration and environmental studies.

What is the difference between Remote Seismic Data Processing vs Remote Geophysical Data Analysis?

AspectRemote Seismic Data ProcessingRemote Geophysical Data Analysis
CredentialsGeophysics degree, data processing certificationsGeophysics or related degree, analysis certifications
Work EnvironmentRemote, computer-based, specialized softwareRemote, data interpretation, software tools
Industry UsageOil & gas, mineral exploration, earthquake monitoringEnvironmental studies, resource exploration, hazard assessment

Remote Seismic Data Processing focuses on handling raw seismic data to prepare it for interpretation, while Remote Geophysical Data Analysis involves interpreting processed data to identify subsurface features. Both roles require geophysical knowledge and often overlap in industry applications, but processing emphasizes data preparation, whereas analysis emphasizes interpretation.

What are the most commonly searched types of Seismic Data Processing jobs in Missouri? The most popular types of Seismic Data Processing jobs in Missouri are:
What are popular job titles related to Remote Seismic Data Processing jobs in Missouri? For Remote Seismic Data Processing jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Remote Seismic Data Processing jobs in Missouri look for? The top searched job categories for Remote Seismic Data Processing jobs in Missouri are:
What cities in Missouri are hiring for Remote Seismic Data Processing jobs? Cities in Missouri with the most Remote Seismic Data Processing job openings:
Data Engineer

Data Engineer

nimble

Chesterfield, MO โ€ข On-site, Remote

$113K - $136K/yr

Other

Posted 15 days ago


Job description

Description


Data Engineer

Chesterfield Office Hybrid or Remote


Why You'll Want to Join!ย 


Join a leading Revenue Cycle Management (RCM) company dedicated to transforming healthcare data into actionable insights. We leverage cutting-edge technology to streamline financial and operational processes, improving efficiency and patient outcomes. We are looking for a Data Engineer to help optimize data pipelines and build a next-generation data infrastructure incorporating technologies such as Microsoft Fabric, Azure Synapse, Databricks, and Snowflake.


Position Overview


Lead the modernization of our data infrastructure as a Data Engineer for nimble. You'll architect scalable cloud-native pipelines using Microsoft Fabric and Databricks to transform healthcare data-claims, EMR/EHR, HL7/FHIR-into actionable insights that drive revenue cycle optimization and clinical outcomes.


Why This Role Matters


Healthcare data engineering is mission-critical: clean, governed data flows directly impact financial accuracy, compliance, and the decisions that improve patient care. Your ETL/ELT pipelines enable our analytics and data science teams to unlock the full potential of healthcare data.


Key Responsibilities


Design, build, and optimize ETL/ELT pipelines using Azure Synapse, Databricks, and Snowflake

Develop robust data models and schemas for healthcare datasets, including claims, EMR/EHR, HL7, and FHIR standards

Write and optimize SQL queries for performance across large healthcare datasets

Implement data governance, quality frameworks, and HIPAA compliance controls

Collaborate with analytics, data science, and business teams to define data requirements

Monitor and troubleshoot data pipeline health and performance

Develop Python or Scala code for complex transformations and data processing

Support Power BI and analytics teams with data modeling and performance optimization

Document data lineage, transformations, and technical architecture

Requirements


3+ years of professional data engineering or ETL/ELT development experience

Expert-level SQL skills with proven optimization experience

Proficiency in Python, Scala, or similar data processing languages

Hands-on experience with cloud data platforms (Azure Synapse, Snowflake, Databricks, or equivalent)

Understanding of healthcare data standards (HL7, FHIR, claims data structures)

Strong grasp of data modeling, normalization, and schema design

Experience with data versioning, CI/CD pipelines, and data quality frameworks


Preferred Qualifications


Experience with Microsoft Fabric or Azure Data Factory

Knowledge of HIPAA compliance and healthcare data security

Background in healthcare, RCM, or claims processing

Experience with dbt (data build tool) or equivalent transformation frameworks

Exposure to dimensional modeling and data warehousing best practices


What Success Looks Like


In 90 days: Deploy first cloud pipeline to production; complete HIPAA training; establish data quality baseline metrics

In 6 months: Reduce data pipeline latency by 30%; expand healthcare data models to include new sources; build reusable transformation components

Ongoing: Maintain 99.5%+ pipeline uptime; mentor junior engineers; drive architectural improvements for scale and performance