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Full Time Data Engineering Jobs in Houston, TX (NOW HIRING)

NAVA Software Solutions

Principal Data Engineer

Houston, TX · On-site

$106K - $127K/yr

Houston, TX - 4 days/week onsite Duration: Full time / Direct Hire The Principal Data Engineer within the Data Science and Analytics team, plays a crucial role in architecting, implementing, and ...

Hp

Data Solutions - Data Engineer

Spring, TX · On-site

$130K - $205K/yr

Represents the data engineering team for all phases of larger and more-complex development projects ... Job - Data & Information Technology Schedule - Full time Shift - No shift premium (United States of ...

Beusa Energy Group

Data Engineer III

The Woodlands, TX · On-site

$104K - $125K/yr

Data Technology Job Status: Full Time FLSA Status: Salary Exempt Reports To: Data Engineering Supervisor Location: The Woodlands, TX Amount of Travel Required: 5-10% Work Schedule: Monday-Friday, 8 a ...

Fervo Energy Company

Data Engineer

Houston, TX · On-site

$109K - $131K/yr

Job Type Full-time Description Fervo is building the most cost-effective, repeatable geothermal ... Working across Data Science, AI Engineering, IT Infrastructure, domain SMEs, and business ...

YO AI Labs

Snowflake Data Architect

Houston, TX

$61 - $78.25/hr

Job Type: Full-Time Must Haves: * Strong Snowflake Data Architecture experience. * Data Governance ... Strong experience in data engineering, data modeling, ETL/ELT, and cloud data platform development.

MetroNational

Data Engineer

Houston, TX · On-site

$109K - $131K/yr

Job Type Full-time Description Position is located onsite in Houston, Texas. Remote candidates will ... Bachelor's degree, advance degree a plus. * 5+ years of hands-on experience in data engineering ...

NAVA Software Solutions

Sr Data Developer

Houston, TX · On-site

Houston TX - 2 days/week hybrid Type: Full time/Direct Hire As the Senior Data Developer, you will: * Implement and maintain consistently available database systems * Develop and maintain data models ...

Vitol

Python Data Engineer

Houston, TX

... full-time role. This role will have the opportunity to interface directly with our traders ... Experience with Data Engineering and building data pipelines * Experience scraping websites with ...

Vitol

Python Data Engineer

Houston, TX · On-site

... full-time role. This role will have the opportunity to interface directly with our traders ... Experience with Data Engineering and building data pipelines * Experience scraping websites with ...

Fuze Health

Data Engineer

Texas City, TX

$140K - $175K/yr

At least 4 years of work experience in software engineering * Experience with one or more of the ... Full-time employee benefits include: Dental, vision, and multiple group medical plans to choose ...

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Showing results 1-20

All JobsData Engineering JobsFull Time Data Engineering JobsFull Time Data Engineering Jobs in Houston, TX

Full Time Data Engineering information

See Houston, TX salary details

$42.5K

$123.9K

$169.5K

How much do full time data engineering jobs pay per year?

As of Aug 7, 2026, the average yearly pay for full time data engineering in Houston, TX is $123,876.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,300.00 and $131,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a full time data engineer?

To thrive as a Full Time Data Engineer, you need strong programming skills (such as Python or Java), proficiency in SQL, and a solid understanding of data modeling and ETL processes, usually supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop or Spark), cloud platforms (such as AWS or Azure), and relevant certifications (e.g., Google Cloud Data Engineer) is highly valuable. Excellent problem-solving, communication, and teamwork abilities distinguish top performers in this role. These skills ensure efficient data infrastructure development, reliable data pipelines, and effective collaboration with cross-functional teams to support business objectives.

What is a full time data engineer?

Full time data engineering jobs involve building, managing, and optimizing data pipelines and infrastructure to collect, process, and store large volumes of data for organizations. Data engineers work with technologies like SQL, Python, cloud platforms, and big data tools to ensure data is reliable and accessible for analytics and business decision-making. These roles typically require strong programming skills, knowledge of database systems, and experience with data modeling and ETL (Extract, Transform, Load) processes. Full time positions generally offer benefits and require a standard workweek commitment, often in tech, finance, healthcare, or other data-driven industries.

What is the difference between Full Time Data Engineering vs Part Time Data Engineering?

AspectFull Time Data EngineeringPart Time Data Engineering
Work HoursTypically 40 hours/weekLess than 20 hours/week
CredentialsRelevant degrees, certifications like AWS, GCP, or AzureSame as full-time, but often less emphasis on certifications
Work EnvironmentFull-time employment, often in corporate or tech firmsFreelance or contract basis, flexible locations
Job ResponsibilitiesDesigning, building, maintaining data pipelinesSupporting existing pipelines, smaller projects

Full Time Data Engineering involves a standard 40-hour workweek with comprehensive responsibilities in designing and maintaining data systems. Part Time Data Engineering offers flexible hours, often focusing on specific tasks or projects. Both roles require relevant technical skills and certifications, but full-time positions typically demand more extensive experience and commitment.

What are some common challenges faced by full time data engineers, and how can they be addressed?

Full-time data engineers often encounter challenges such as integrating data from diverse sources, ensuring data quality, and optimizing data pipelines for scalability and performance. These issues can be addressed by adopting robust ETL (Extract, Transform, Load) frameworks, implementing automated data validation tests, and collaborating closely with data analysts and software engineers to align on data requirements. Staying updated with the latest cloud technologies and best practices in data architecture also helps in overcoming these challenges and maintaining efficient, reliable data systems.
What are the most commonly searched types of Data Engineering jobs in Houston, TX? The most popular types of Data Engineering jobs in Houston, TX are:
What cities near Houston, TX are hiring for Full Time Data Engineering jobs? Cities near Houston, TX with the most Full Time Data Engineering job openings:
Full Time Data Engineering jobs near you

Principal Data Engineer

NAVA Software Solutions

Houston, TX • On-site

$106K - $127K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

NAVA Software solutions is looking for a Principal Data Engineer
Details:
Principal Data Engineer
Location: Houston, TX - 4 days/week onsite
Duration: Full time / Direct Hire
The Principal Data Engineer within the Data Science and Analytics team, plays a crucial role in architecting, implementing, and managing robust, scalable data platforms. This position demands a blend of cloud data engineering, systems engineering, data integration, and machine learning systems knowledge to enhance GST's data capabilities, supporting advanced analytics, machine learning projects, and real-time data processing needs. You will guide other team members and collaborate closely with cross-functional teams to design and implement modern data solutions that enable data-driven decision-making across the organization.
As a Principal Data Engineer you will:
  • Collaborate with Business, and IT functional experts to gather requirements or issues, perform gap analysis and recommend/implement process and/or technology improvements to optimize data solutions.
  • Design data solutions on Databricks including Delta Lake, Data Warehouse, Data Mart and others to support the data science and analytical needs of the organization.
  • Design and implement scalable and reliable data pipelines to ingest, process, and store diverse data at scale, using technologies such as Databricks, Apache Spark, Kafka, Flink, AWS Glue or other AWS services.
  • Work within cloud environments like AWS to leverage services including but not limited to EC2, RDS, S3, Athena, Glue, Lambda, EMR, Kinesis, and SQS for efficient data handling and processing.
  • Develop and optimize data models and storage solutions (SQL, NoSQL, Key-Value DBs, Data Lakes) to support operational and analytical applications, ensuring data quality and accessibility.
  • Utilize ETL tools and frameworks (e.g., Apache Airflow, Talend) to automate data workflows, ensuring efficient data integration and timely availability of data for analytics.
  • Implement pipelines with a high degree of automation for data workflows and deployment pipelines using tools like Apache Airflow, Terraform, and CI/CD frameworks.
  • Collaborate closely with business analysts, data scientists, machine learning engineers, and optimization engineers, providing the data infrastructure and tools needed for complex analytical models, leveraging Python, scala or R for data processing scripts.
  • Ensure compliance with data governance, compliance and security policies, implementing best practices in data encryption, masking, and access controls within a cloud environment.
  • Establish best practices for code documentation, testing, and version control, ensuring consistent and reproductive data engineering practices across the team.
  • Monitor and troubleshoot data pipelines and databases for performance issues, applying tuning techniques to optimize data access and throughput.
  • Ensure efficient usage of AWS and Databricks resources to minimize costs while maintaining high performance and scalability.
  • Cross functional work understanding data landscape, developing proof of concepts, and demonstrating to stakeholders.
  • Leads one or more data projects and support with internal and external resources. Coach and mentor junior data engineers.
  • Stay abreast of emerging technologies and methodologies in data engineering, advocating for and implementing improvements to the data ecosystem.

What We Need From You
  • Bachelor's Degree Computer Science, Data Science, MIS, Engineering, Mathematics, Statistics or other quantitative discipline with 5-8 years of hands-on experience in data engineering, with a proven track record in designing and operating large-scale data pipelines and architectures Req
  • Proven experience designing scalable, fault-tolerant data architecture and pipelines on Databricks delta lake, lakehouse, unity catalog, streaming, AWS, ETL/ELT development and data modeling, with a focus on performance optimization and maintainability Required
  • Deep experience of platforms and services like Databricks, and AWS native data offerings Required
  • Solid experience with big data technologies (Databricks, Apache Spark, Kafka) and AWS cloud services related to data processing and storage Required
  • Strong hands-on experience with ETL/ELT pipeline development using AWS tools and Databricks Workflows Required
  • Strong experience in AWS cloud services, with hands-on experience in integrating cloud storage and compute services with Databricks Required
  • Proficient in SQL and programming languages relevant to data engineering (Python, Java, Scala Required
  • Hands on RDBMS and data warehousing experience (data modeling, analysis, programming, stored procedures) Required
  • Good understanding of system architecture and design patterns to design and develop applications using these principles Required
  • Proficiency with version control systems like Git and experience with CI/CD pipelines for automating data engineering deployments Required
  • Familiarity with machine learning model deployment and management practices is a plus Preferred
  • Experience with SAP, BW, HANA, Tableau, or Power BI is a plus Preferred
  • Experience with auto, manufacturing, or supply chain industries is a plus Preferred
  • Project life-cycle leadership and support for requirement workshop, design, development, test cycles and production cutover, post-go live support, and environment strategy. Strong knowledge of agile methodologies Required
  • Strong communication skills, capable of collaborating effectively across technical and non-technical teams in a fast-paced environment. Required
  • AWS Certified Solution Architect Preferred
  • Databricks Certified Associate Developer for Apache Spark Preferred or other relevant certifications. Preferred
NAVA Software Solutions logo

About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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