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Staff Data Engineer Jobs (NOW HIRING)

As a Staff Data Engineer, you will collaborate closely with all team members to create a modular, scalable solution that addresses current needs, but will also serve as a foundation for future ...

As a Staff Data Engineer, you will collaborate closely with all team members to create a modular, scalable solution that addresses current needs, but will also serve as a foundation for future ...

As a Staff Data Engineer, you will collaborate closely with all team members to create a modular, scalable solution that addresses current needs, but will also serve as a foundation for future ...

As a Staff Data Engineer, you will collaborate closely with all team members to create a modular, scalable solution that addresses current needs, but will also serve as a foundation for future ...

As a "Staff Data Engineer", you should be able to technically help and assist team to steer through correct technical directions following the best practices. You will have deeper understanding of ...

Staff Data Engineer

$117K - $140K/yr

The Staff Data Engineer role is part of the Bamboo Health Engineering Team. You would serve as a lead engineer responsible for building and supporting Data Warehousing and reporting functions. As ...

Staff Data Engineer

Brooklyn, NY · On-site

$151K - $177K/yr

Job Purpose As a Staff Data Engineer, you will be part of a Data Engineering team that is focused on making critical data at National Grid available to our business teams. Using the agile framework ...

About The Role As our Staff Data Engineer , you will own and evolve the foundational data systems that power NexHealth's analytics and unlock the next generation of customer-facing insights. This is ...

OR · On-site

$180K - $200K/yr

What You'll Do As a Staff Data Engineer at Imagine Pediatrics, you will be the first dedicated Data Engineer on a hybrid team with Analytics Engineers, responsible for defining how data moves through ...

Staff Data Engineer

San Diego, CA · On-site

$121K - $146K/yr

The Role As Staff Data Engineer, you will provide senior onshore technical leadership for the data engineering team. You will own a defined slice of our centralized Databricks data platform with full ...

The Staff Data Engineer is an expert data handler and developer who has demonstrated their capacity for solving problems of broad scope that support the success of their value stream. The Staff Data ...

ABOUT THE TEAM As a Staff Data Engineer on the Analytics Team, you will be collaborating with stakeholders across the company to design, build and implement data pipelines and models that enable our ...

Staff Data Engineer

New York, NY · On-site

$212K - $265K/yr

About Data Engineering at Headway Headway is looking for a Staff Data Engineer to help us get closer to executing our mission: to create access to affordable, quality mental healthcare across the ...

What You'll Do As a Staff Data Engineer at Imagine Pediatrics, you will be the first dedicated Data Engineer on a hybrid team with Analytics Engineers, responsible for defining how data moves through ...

As a Staff Data Engineer, you will own the technical architecture and production runtime of JobNimbus's enterprise integration portfolio and external data engine. This is a heavy backend systems ...

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Staff Data Engineer information

See salary details

$23K

$99.3K

$192.5K

How much do staff data engineer jobs pay per year?

As of Jul 7, 2026, the average yearly pay for staff data engineer in the United States is $99,330.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,000.00 and $125,000.00 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.
More about Staff Data Engineer jobs
What cities are hiring for Staff Data Engineer jobs? Cities with the most Staff Data Engineer job openings:
What states have the most Staff Data Engineer jobs? States with the most job openings for Staff Data Engineer jobs include:
Infographic showing various Staff Data Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $99,330 per year, or $47.8 per hour.
Staff Data Engineer

Staff Data Engineer

HCA Healthcare

Franklin, TN • On-site

Other

Posted 27 days ago


HCA Healthcare rating

6.4

Company rating: 6.4 out of 10

Based on 2,222 frontline employees who took The Breakroom Quiz

636th of 877 rated healthcare providers


Job description

This is OUR story... and YOUR next chapterAt HCA Healthcare, our Digital Transformation and Innovation (DT&I) team is redefining what’s possible inpatient care. By leveraging the power of artificial intelligence, automation, and digital technologies, DT&I is helping drive meaningful improvements in clinical outcomes, reduce manual workload, and expand the reach of our care teams. If you're passionate about using technology to improve human life, this is where your work truly mattersWhat you will accomplish in this role Job Summary and Qualifications

The Staff Data Engineer serves as a primary development resource for design, writing code, test, implementation, document functionality, and maintain of NextGen solutions for the GCP Cloud enterprise data initiatives. The role requires working closely with data teams, frequently in a matrixed environment as part of a broader project team. This role requires ‘self-starters’ who are proficient in problem solving and capable of bringing clarity to complex situations. The culture of the organization places an emphasis on teamwork, so social and interpersonal skills are equally important as technical capability. Due to the emerging and fast-evolving nature of GCP technology and practice, the position requires that one stay well-informed of technological advancements and be proficient at putting new innovations into effective practice.

In addition, this candidate will have a history of increasing responsibility in a small multi-role team. This position requires a candidate who can analyze business requirements, perform design tasks, construct, test, and implement solutions with minimal supervision. This candidate will have a record of accomplishment of participation in successful projects in a fast-paced, mixed team (consultant and employee) environment. In addition, the applicant must be willing to mentor other developers to prepare them for assuming the responsibilities.


As a Staff Data Engineer, you will collaborate closely with all team members to create a modular, scalable solution that addresses current needs, but will also serve as a foundation for future success. The position will be critical in building the team’s engineering practices in test driven development, continuous integration, and automated deployment and is a hands-on team member who actively coaches the team to solve complex problems.

In addition, the Staff Data Engineer will be expected to leverage AI-native workflows to accelerate solution delivery. This includes the ability to use AI-assisted development tools for rapid software engineering, apply modern AI building blocks such as prompting, retrieval-augmented generation (RAG), evaluation frameworks, agentic workflows, and machine learning, and to rapidly prototype and iterate on data-driven applications.

What you will do:

At HCA DT&I, your deliverables will influence patient care. Every process, technology, and decision matters. This role will provide application development for specific business environments. Focus on setting technical direction on groups of applications and similar technologies as well as taking responsibility for technically robust solutions encompassing all business, architecture, and technology constraints.

  • Work with data engineers, data architects, data scientists, and other internal stakeholders to understand product requirements and then design, build, and monitor data platforms and pipelines that meet today's requirements but can gracefully scale.

  • Implement automated workflows that lower manual/operational costs, define and uphold SLAs for timely delivery of data, and move the company closer to democratizing data.
  • Enable a self-service data architecture supporting query exploration, dashboards, data catalog, and rich data discovery.
  • Promote a collaborative team environment that prioritizes effective communication, team member growth, and success of the team over success of the individual.
  • Design and create real-time data pipelines that accelerate the time from idea to insight.
  • Adheres to and supports data engineering best practices, processes, and standards.
  • Produce high quality, modular, reusable code that incorporates best practices and serves as an example for less experienced engineers.
  • Helps promote and support data security best practices that align with industry standards and regulatory and legal requirements.
  • Help mentor team members on complex data projects and following the Agile process.
  • Help lead data analysis efforts and solution proposals to data related and data architecture problems.
  • Help lead implementation of unit and integration tests and promote and conduct performance testing where appropriate.
  • Be a leader in the HCA data community. Evangelize data engineering best practices and standards, participate, or present at community events, and encourage the continual growth and development of others.
  • Be curious. Be growth minded. Encourage and enable this in others.
  • Demonstrate professional and personal maturity through self-leadership.
  • Build productive and healthy relationships within the department and other teams to foster growth of our culture, our people, and our platforms.
  • Practices and adheres to the “Code of Conduct” philosophy and “Mission and Value Statement.”
  • Perform other duties as assigned.
  • Responsible for building and supporting a GCP based ecosystem designed for enterprise-wide analysis of structured, semi-structured, and unstructured data.
  • Work independently, and complete tasks on-schedule by exercising strong judgment and problem-solving skills.
  • Analyze requirements, design AI/ML based solutions, and integrate those solutions for customer environments.
  • Proven experience effectively prioritizing workload to meet deadlines and work objectives.
  • Works in an environment with rapidly changing business requirements and priorities
  • Shares knowledge and experience to contribute to growth of overall team capabilities.
  • Actively participate in technical group discussions and adopt any modern technologies to improve the development and operations.
  • Apply AI-native engineering practices to design, implement, and optimize data and software systems, accelerating time-to-value.
  • Incorporate prompt engineering, RAG pipelines, and automated evaluation techniques into data solutions and workflows.
  • Prototype, test, and iterate rapidly using AI-assisted development approaches, ensuring scalable and reliable production systems.
  • Explore and integrate agentic workflows and emerging AI/ML capabilities to enhance automation and decision-making across platforms.

What you will need to have:

  • Bachelor's degree in computer science, related technical field, or equivalent experience required

  • Master's degree in computer science or related field preferred
  • 5+ years of experience as a Data Engineer required
  • 1+ year(s) of experience in healthcare preferred
  • 7+ years of experience in information technology required
  • Demonstrates an empathetic and growth mindset with a willingness to learn new skills, technologies, and methodologies. required
  • Strong knowledge of public cloud best practices and design patterns used in creating, automating, and supporting data pipelines. required
  • Strong ability to assemble large, complex sets of data that meet functional and non-functional product requirements. required
  • Strong ability to identify, design, and implement internal process improvements including redesigning data platforms for greater scalability, optimized data delivery, and automating manual processes. required
  • Strong ability to create and use analytical tools to monitor data pipeline metrics and provide actionable intelligence to increase operational efficiency and valuable data outcomes. required
  • Strong ability to present and facilitate technical ideas. required
  • Expert ability using source control management tools such as Git/GitHub. required
  • Expert ability using CI/CD automation tools. required
  • Strong understanding of SQL and analytical data warehouses. required
  • Strong understanding of Agile methodologies and how to apply Agile within the team. required
  • Helps coach and mentor junior team members and others external to the team. required
  • Proven ability to complete work, make sound decisions, and plan and accomplish goals without explicit direction/guidance from leadership. required
  • Builds and nurtures healthy relationships with all colleagues. required
  • Stays abreast of public cloud technologies, capabilities, and industry use of public cloud to help guide HCA’s strategy and adoption. required
  • Demonstrates productive and inclusive communication skills with all colleagues. required
  • Excellent problem-solving and analytical skills. required
  • Experience applying prompt engineering techniques to improve accuracy and efficiency of AI-assisted solutions. required
  • Strong ability to prototype and iterate using AI-assisted development tools (e.g., Copilot, ChatGPT, or equivalent). required
  • 2+ years hands-on experience with GCP platform and experience with many of the following components:

Cloud Run, GKE, Cloud Functions


Pub/Sub,Bigtable, Cloud SQL, Cloud Spanner

BigQuery, Dataflow, Data Fusion

Cloud Composer, DataProc, CI/CD, Cloud Logging

Vertex AI, NLP, GitHub

  • 4+ Years of hands-on experience with many of the following components:

 Spark Streaming, Kafka


SQL, JSON, Avro, Parquet

Java, Python, or Scala

  • 18+ months of hands-on experience with many of the following components:

Hands-on experience with AI-assisted development tools (e.g., Copilot, ChatGPT, or equivalent) to accelerate engineering tasks.

  • Familiarity with modern AI application patterns such as prompting strategies, RAG, evals, and agent-based systems.
  • Demonstrated ability to rapidly prototype and iterate with AI/ML technologies to deliver practical, production-ready solutions.
  • A growth mindset with curiosity to experiment with emerging AI frameworks and incorporate them into engineering practices.

Certifications (a plus, but not required): GCP Cloud Professional Data Engineer


"There is so much good to do in the world and so many different ways to do it."- Dr. Thomas Frist, Sr.
HCA Healthcare Co-Founder

If you find this opportunity compelling, we encourage you to apply for our Staff Data Engineer opening. We promptly review all applications. Highly qualified candidates will be directly contacted by a member of our team.We are interviewing apply today!

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.




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