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Senior Data Engineer Jobs in Spring, TX (NOW HIRING)

ComboCurve, Inc.

Senior Data Engineer, Python

Houston, TX · On-site +1

$109.30K - $131.30K/yr

We are seeking a highly analytical and experienced Senior Data Engineer to help optimize production forecasting and operations scheduling within the petroleum engineering domain. You'll bridge the ...

SunStrong Management, LLC

Senior Data Engineer

Houston, TX · Remote

$108.50K - $147.40K/yr

Job SummaryThe Data Engineer - Asset Management Analytics supports internal Asset Management and Asset Accounting customers by delivering AI-driven analytics products that support asset onboarding ...

SunStrong Management LLC

Senior Data Engineer

Houston, TX · On-site +1

$101.20K - $137.50K/yr

Job Summary The Data Engineer - Asset Management Analytics supports internal Asset Management and Asset Accounting customers by delivering AI-driven analytics products that support asset onboarding ...

Parkhill

Senior Data Scientist

Houston, TX

The Senior Data Scientist will leverage advanced analytics, machine learning, and AI to generate ... We are more than planners, architects, and engineers -- we are neighbors who choose to live and ...

Parkhill

Senior Data Scientist

Houston, TX · On-site

Overview The Senior Data Scientist will leverage advanced analytics, machine learning, and AI to ... We are more than planners, architects, and engineers - we are neighbors who choose to live and work ...

Parkhill

Senior Data Scientist

Houston, TX

Overview The Senior Data Scientist will leverage advanced analytics, machine learning, and AI to ... We are more than planners, architects, and engineers - we are neighbors who choose to live and work ...

Parkhill

Senior Data Scientist

Houston, TX · On-site +1

Overview The Senior Data Scientist will leverage advanced analytics, machine learning, and AI to ... We are more than planners, architects, and engineers - we are neighbors who choose to live and work ...

SupplyHouse

Sr. Data Architect

Houston, TX

$145K - $180K/yr

As a strategic individual contributor, the Sr. Data Architect will partner with executive leadership, Engineering, Analytics, Security, and Product teams to ensure data is reliable, secure, governed ...

NOV, Inc.

Senior Data Scientist

Houston, TX · On-site

Reports to: VP Data & Analytics As a Senior Data Scientist , you will: * Partner with business ... Utilize programming languages such as SQL, Python for data manipulation, analysis and model ...

NOV, Inc.

Senior Data Scientist

Houston, TX · On-site

Reports to: VP Data & Analytics As a Senior Data Scientist , you will: * Partner with business ... Utilize programming languages such as SQL, Python for data manipulation, analysis and model ...

Deloitte

Sr Databricks Data Engineer

Houston, TX

$109.30K - $131.30K/yr

As a Senior Consultant - Databricks Engineer in our AI & Data practice, you will design, build, and optimize cloud-based data engineering solutions that support large-scale transformation. You will ...

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Senior Data Engineer information

See Spring, TX salary details

$72.1K

$112.4K

$155.7K

How much do senior data engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for senior data engineer in Spring, TX is $112,418.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,300.00 and $128,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Data Engineer, and why are they important?

To thrive as a Senior Data Engineer, you need strong expertise in data modeling, ETL development, programming (such as Python or Scala), and a degree in computer science or a related field. Proficiency with big data technologies (like Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and database systems, as well as relevant certifications, is highly valuable. Excellent problem-solving, communication, and leadership skills help you collaborate across teams and mentor junior engineers. These skills and qualities ensure robust, scalable data solutions that support organizational decision-making and growth.

What are some common challenges Senior Data Engineers face when integrating data from multiple sources?

Senior Data Engineers often encounter challenges such as inconsistent data formats, varying data quality, and differing update frequencies when integrating data from multiple sources. Addressing these issues requires designing robust ETL (Extract, Transform, Load) pipelines, implementing data validation checks, and collaborating closely with source system owners to ensure data integrity. Effective communication with cross-functional teams and leveraging scalable data integration tools are also essential to streamline the process and minimize errors.

What are Senior Data Engineers?

Senior Data Engineers are experienced professionals who design, build, and maintain large-scale data processing systems and infrastructure. They are responsible for developing data pipelines, managing databases, and ensuring the efficient flow and integrity of data across various platforms. Senior Data Engineers often collaborate with data scientists, analysts, and other engineers to support business intelligence and machine learning projects. They also play a key role in implementing best practices for data security, quality, and governance within an organization.

What is the difference between Senior Data Engineer vs Data Scientist?

AspectSenior Data EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with data pipelinesBachelor's/Master's in CS, Statistics, or related; proficiency in statistical analysis and modeling
Work EnvironmentBuild and maintain data infrastructure, optimize data workflowsAnalyze data, develop predictive models, generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data engineering is essentialResearch, marketing, tech firms focusing on data analysis and modeling

While both roles work with data, Senior Data Engineers focus on developing and maintaining data infrastructure, whereas Data Scientists analyze data to generate insights and build models. They often collaborate but have distinct skill sets and responsibilities.

What are the most commonly searched types of Data Engineer jobs in Spring, TX? The most popular types of Data Engineer jobs in Spring, TX are:
What are popular job titles related to Senior Data Engineer jobs in Spring, TX? For Senior Data Engineer jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Senior Data Engineer jobs in Spring, TX look for? The top searched job categories for Senior Data Engineer jobs in Spring, TX are:
What cities near Spring, TX are hiring for Senior Data Engineer jobs? Cities near Spring, TX with the most Senior Data Engineer job openings:
Senior Data Engineer jobs near you
Senior Data Engineer, Python

Senior Data Engineer, Python

ComboCurve, Inc.

Houston, TX • On-site, Remote

$109.30K - $131.30K/yr

Full-time

Posted 18 days ago

Job description

ComboCurve is a industry leading cloud-based software solution for A&D, reservoir management, and forecasting in the energy sector. Our platform empowers professionals to evaluate assets, optimize workflows, and manage reserves efficiently, all in one integrated environment.
By streamlining data integration and enhancing collaboration, we help operators, engineers, and financial teams make informed decisions faster. Trusted by top energy companies, ComboCurve delivers real-time analytics and exceptional user support, with a world-class customer experience team that responds to inquiries in under 5 minutes.
We are seeking a highly analytical and experienced Senior Data Engineer to help optimize production forecasting and operations scheduling within the petroleum engineering domain. You'll bridge the gap between complex mathematical models (reservoir dynamics, optimization, logistics) and robust, cloud-scale data systems.
This role requires a unique combination of deep Python expertise, mastery of modern data processing and API frameworks, and a strong foundational understanding of mathematics, reasoning, and petroleum engineering principles.
Responsibilities
Data Architecture & Engineering
  • Design, build, and maintain scalable data pipelines for ingesting, transforming, and validating time-series data related to well performance, sensor readings, and operational logs.
  • Develop robust, high-performance data models using PyArrow and Pandas for efficient analysis and transfer.
  • Implement data quality and schema validation using Pydantic to ensure data integrity across all stages of the pipeline.
  • Manage and optimize data storage and retrieval in MongoDB, and integrate with cloud-native platforms like GCP BigQuery or Snowflake where applicable.

API & Application Development
  • Build, deploy, and maintain high-performance asynchronous microservices and prototypes using FastAPI or Flask to serve complex optimization and scheduling model predictions.
  • Use Postman for testing, documenting, and automating API workflows.
  • Containerize and orchestrate applications using Docker and manage deployment on Google Cloud Platform (GCP).

Quantitative Analysis & Optimization
  • Collaborate with reservoir and operations teams to translate complex scheduling and logistics problems into mathematical models (e.g., linear programming, resource allocation).
  • Implement numerical routines and simulations efficiently using NumPy for use in production environments.
  • Apply strong logical and analytical reasoning to debug, validate, and interpret the outputs of operational scheduling algorithms.

Requirements
  • Education: Bachelor's or Master's degree in Petroleum Engineering, Computer Science, Mathematics, Operations Research, or related quantitative field, or equivalent experience.
  • Quantitative Strength: Proven ability to work with mathematical modeling, optimization, and time-series analysis, including:

o Linear and Mixed-Integer Programming
o Probability and Statistics
o Algorithmic Complexity and Performance Reasoning
  • Collaborative mindset - experience working closely with data scientists, product owners, and domain experts to deliver production-ready systems.

Preferred Qualifications
  • Domain Expertise: Solid understanding of well operations, drilling logistics, production data, and scheduling workflows.
  • Experience working with large-scale or streaming datasets.
  • Experience with mathematical modeling and optimization libraries (SciPy, PuLP, OR-Tools).
  • Experience setting up CI/CD pipelines and container deployments on GCP.

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