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Staff Data Engineer Jobs in Texas (NOW HIRING)

As our Staff Data Engineer, you will be responsible for organizing plans that drive outcomes and making a direct impact on our mission. We want you to provide technical leadership to your teammates ...

Dallas, TX Summary The Staff Data Engineer, MLOps leads the design, build, and optimization of Hershey's machine learning operations platform-enabling data science and AI teams to develop, deploy ...

Staff Data Engineer

Leander, TX · On-site +1

$130K - $150K/yr

We are looking for a Staff Data Engineer to transform millions of data points into unparalleled opportunities - supporting everything from electing Democrats to combating climate change throughout ...

Staff Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Staff Data Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems. In this role, engineers spend a significant portion of their time ...

Staff Data Engineer

Austin, TX · On-site

$160K - $195K/yr

As our Staff Data Engineer, you will be responsible for organizing plans that drive outcomes and making a direct impact on our mission. We want you to provide technical leadership to your teammates ...

Staff Data Platform Engineer

Austin, TX · On-site +1

$113K - $136K/yr

The Staff Data Platform Engineer role at Flo blends Data Engineering, Backend Engineering, and Cloud Engineering into a unique and impactful position. This position is expected to design, build, and ...

The Opportunity We're looking for a Staff Data Engineer to help shape the future of Honor's data platform. This role is focused on building the foundational data platform that powers analytics ...

Role Summary We are looking for a Staff Data Science Engineer to lead the design and delivery of scalable data science, machine learning, and analytics solutions that create measurable business value ...

Data Engineer

Houston, TX

$109K - $131K/yr

STRATEGIC STAFFING SOLUTIONS HAS AN OPENING. This is a Contract Opportunity with our company that ... Data Engineer Location: Houston, TX Contract Length: 12+ Months Job ref# 247245 Seeking a Senior ...

Data Engineer

Houston, TX · On-site

$109K - $131K/yr

STRATEGIC STAFFING SOLUTIONS HAS AN OPENING! This is a Contract Opportunity with our company that ... Data Engineer Location: Houston, TX Contract Length: 12+ Months Pay: 80-90 per hr on W2 Job ref ...

They are seeking a Staff Data Science Engineer to lead the design and delivery of scalable data science, machine learning, and analytics solutions that create measurable business value across the ...

About the Role CharterUP is seeking a Staff Data Scientist to advance our data science capabilities ... Work with Engineering to embed elasticity models, demand forecasts, and operator availability logic ...

Staff Data Scientist Reports to: Chief Product Officer Location: This position is based in Austin ... Work with Engineering to embed elasticity models, demand forecasts, and operator availability logic ...

... value.  As a Staff Data Scientist, you will play an essential part in advancing Schwab ... Set and elevate engineering standards for data science  by establishing best practices that ...

Data Engineer

Plano, TX · On-site

$110K - $132K/yr

Alpha Consulting Corp. is seeking a skilled Data Engineer with a background in AWS and GCP to join ... clinical staffing business since 1994. Founded in 1994, the company is headquartered in East ...

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Staff Data Engineer information

See Texas salary details

$21.4K

$92.5K

$179.3K

How much do staff data engineer jobs pay per year?

As of Aug 2, 2026, the average yearly pay for staff data engineer in Texas is $92,541.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,300.00 and $116,500.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior staff data engineers or principal data engineers with extensive experience, advanced skills in big data tools, and leadership responsibilities can earn $500,000 or more annually. Such compensation often includes base salary, bonuses, and stock options, typically in large tech companies or organizations with high data maturity. Achieving this level usually requires years of experience, specialized expertise, and a strong track record of delivering complex data solutions.

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

To thrive as a Staff Data Engineer, you need advanced proficiency in data architecture, programming (such as Python, Java, or Scala), and experience with large-scale data systems, supported by a bachelor's or master's degree in computer science or a related field. Familiarity with big data tools (Hadoop, Spark), cloud platforms (AWS, GCP, or Azure), and relevant certifications like Google Professional Data Engineer or AWS Data Analytics are typically required. Strong problem-solving abilities, effective communication, and leadership skills help drive cross-functional projects and mentor junior engineers. These skills ensure the design, implementation, and maintenance of robust data infrastructure that supports organizational decision-making and scalability.

What are Staff Data Engineers?

Staff Data Engineers are senior-level professionals responsible for designing, building, and maintaining large-scale data processing systems and architectures. They often lead technical initiatives, set data engineering standards, and mentor other engineers within a company. Staff Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure reliable and efficient data pipelines. Their role requires deep expertise in data modeling, ETL processes, distributed systems, and cloud technologies. They play a crucial part in enabling organizations to make data-driven decisions at scale.

How does a Staff Data Engineer typically collaborate with cross-functional teams to deliver data-driven solutions?

As a Staff Data Engineer, you’ll frequently partner with data scientists, analysts, and product managers to understand project requirements and design scalable data systems. You'll be responsible for translating business needs into technical specifications, recommending best practices, and mentoring junior engineers. Collaboration often involves participating in sprint planning, code reviews, and architecture discussions to ensure data solutions are robust, secure, and aligned with organizational goals. Effective communication and a proactive approach to problem-solving are key to successful collaboration in this role.

Can I make 200K as a data engineer?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in tools like Spark or Hadoop can potentially earn salaries of $200,000 or more, especially in high-cost-of-living areas or at large organizations. Entry-level or mid-level data engineers typically earn lower salaries, and reaching a $200,000 salary often requires several years of experience and specialized knowledge.

What engineers make $300,000 a year?

Senior data engineers, especially those with extensive experience, advanced skills in cloud platforms, and expertise in big data tools, can earn $300,000 or more annually. High compensation is often associated with roles in large organizations, specialized industries, or those holding leadership responsibilities and advanced certifications.

What is the difference between Staff Data Engineer vs Data Engineer?

AspectStaff Data EngineerData Engineer
Required CredentialsBachelor's or Master's in CS, experience with big data toolsBachelor's in CS or related field, some experience with data pipelines
Work EnvironmentSenior-level, cross-team collaboration, leadership rolesEntry to mid-level, focused on building data pipelines
Employer & Industry UsageTech companies, large enterprises, data-driven organizationsStartups, small to medium enterprises, tech firms

The main difference is that a Staff Data Engineer typically has more experience, leadership responsibilities, and works on complex projects across teams, whereas a Data Engineer focuses on developing and maintaining data pipelines at an operational level.

What does a staff data engineer do?

A staff data engineer designs, develops, and maintains large-scale data systems and pipelines to support data analysis and business decision-making. They often lead data architecture initiatives, optimize data workflows, and collaborate with data scientists and engineers using tools like SQL, Spark, and cloud platforms. This role typically requires strong programming skills, experience with data modeling, and a deep understanding of data governance and security practices.
What cities in Texas are hiring for Staff Data Engineer jobs? Cities in Texas with the most Staff Data Engineer job openings:
Infographic showing various Staff Data Engineer job openings in Texas as of July 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $92,541 per year, or $44.5 per hour.

$160K - $195K/yr

Other

Re-posted 24 days ago


Job description

About the Role:

As our Staff Data Engineer, you will be responsible for organizing plans that drive outcomes and making a direct impact on our mission. We want you to provide technical leadership to your teammates through coaching and mentorship, and collaborate cross-functionally to implement impactful improvements to our product.

As part of the Self Financial Data Engineering Team, your role will be to ensure that data remains a strategic asset for Self Financial by delivering timely, high-quality, and purpose-built data to our team members. Our team supports Self Financial's internal Analytics, Machine Learning, and Business Intelligence organizations.

What you will do:

  • Operates as part of a cross functional product development team that includes Architecture, Infrastructure, and Product Management
  • Your primary focus will be on leading the data pipeline, modeling, and populating data schemas within Self Financial's Data Environment for use in business intelligence and data analysis activities.
  • Your day-to-day activities will include:
    • Collaborating closely with Product Management to translate Self Financial's strategic vision into actionable projects.
    • Architecture design, project analysis, work break down and planning.  
    • Creating Physical and Logical Data Models with large, complex data sets
    • Managing data pipeline, ETL/ELT processes using SQL and Python
    • Maintaining data lifecycle and quality standards

Who you are:

  • 8+ years of experience with database development, database integration, and data analytics tools
  • 8+ years of experience designing and implementing complex Data Warehouse and Data Lake data models (Kimball)
  • Willingness to embrace the responsibilities of team leadership and accountability for team results
  • Proficient in managing Data ETL/ELT with large data sets
  • Experience with columnar data structures such as Amazon RedShift
  • Familiarity with AWS data warehousing tools
  • Experience with common software engineering tools such as Git, JIRA, Confluence and similar platforms
  • Familiarity with Apache Airflow and Python
  • Excellent listening, interpersonal, written, and oral communication skills

Base salary range: $160,000-195,000 annually.  Individual pay and level is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.