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Staff Data Engineer Jobs in Florida (NOW HIRING)

We're looking for a Staff Data Engineer to lead the design, development, and operation of AI agents that power intelligent experiences across the Material Bank platform. This role sits at the ...

We're looking for a Staff Data Engineer to lead the design, development, and operation of AI agents that power intelligent experiences across the Material Bank platform. This role sits at the ...

Sr. Staff Software Engineer- Eng

Sunrise, FL · On-site

$116K - $154K/yr

Senior Staff Data Engineer - FinOps Platform & Reporting Location: ATL / FL (Weston or Sunrise) / MA About the Role As a Senior Staff Data Engineer - FinOps Platform & Reporting, you will lead the ...

Staff Data Scientist

Melbourne, FL · On-site

$168.20 - $252.20/hr

Northrop Grumman Aerospace Systems has an opening for a Staff Data Scientist Instrumentation/Staff ... Perform a variety of duties, including: engineering design tasks as assigned, participating in ...

Data Engineer

Coral Springs, FL · On-site

$109K - $130K/yr

As a Data Engineer, you will be responsible for collecting, analyzing, and interpreting data to provide valuable insights to our organization. You will work closely with various teams to extract ...

Data Engineer

Fort Lauderdale, FL · On-site

$109K - $131K/yr

Summary: The Data Engineer supports operations and conducts data analytics projects to provide information and insights to stakeholders for decision-making or solution development. This role ...

Data Engineer

Miami, FL · On-site

$104K - $125K/yr

Engages and communicates effectively with a variety of IT, research, and medical staff ... data engineering and integration experience * 1-3 years of data management in cloud-based data ...

Data Engineer

Jacksonville, FL · On-site

$106K - $127K/yr

We are seeking a Data Engineer to design, develop, and maintain modern data solutions that support enterprise reporting, analytics, and operational decision-making. This role is responsible for ...

Data Engineer

Miami, FL · On-site

$109K - $131K/yr

Engages and communicates effectively with a variety of IT, research, and medical staff ... data engineering and integration experience * 1-3 years of data management in cloud-based data ...

Data Engineer I

Gainesville, FL · On-site

$65K - $78K/yr

Staff Full-Time Location: Main Campus (Gainesville, FL) Categories: Computer Science, Information Technology, Engineering Department: 14400000 - IT-DATA PLATFORM & ANALYTICS Classification Title: App ...

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Senior Data Engineer

Tallahassee, FL · Remote

$95K - $129K/yr

Our specially trained staff works hand-in-hand with physicians to provide the right products and ... Data Engineering Reports to: Senior Director of Data Platform Engineer Location: Remote ...

Pricing Data Engineer

Miami, FL · On-site

$110K - $169K/yr

The Pricing Data Engineer builds and maintains the data infrastructure and tools that enable ... recognize our staff professionals for their work. Full time positions are eligible for a ...

Job Title Full-Stack Data Engineer Location Doral, FL 33122 US (Primary) Category Intelligence Job Type Full-Time Career Level Staff Education Bachelor's Degree Travel Security Clearance Required TS ...

Network Data Engineer Location : Palm Beach , FL Duration: Fulltime Must Have Technical/Functional Skills • Strong experience with Cisco IOS/XE, Arista EOS, and network automation tools • Hands ...

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Network Data Engineer Location : Palm Beach , FL Duration: Fulltime Must Have Technical/Functional Skills • Strong experience with Cisco IOS/XE, Arista EOS, and network automation tools • Hands ...

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Showing results 1-20

Staff Data Engineer information

See Florida salary details

$17.2K

$74.2K

$143.9K

How much do staff data engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for staff data engineer in Florida is $74,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,600.00 and $93,400.00 per year, depending on experience, location, and employer.

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 is a staff data engineer?

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.

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.

Infographic showing various Staff Data Engineer job openings in Florida as of August 2026, with employment types broken down into 2% As Needed, 77% Full Time, 16% Part Time, 1% Temporary, and 4% Contract. Highlights an 96% Physical, 2% Hybrid, and 2% Remote job distribution, with an average salary of $74,228 per year, or $35.7 per hour.

Staff Data Engineer

Material Bank

Fort Lauderdale, FL • On-site

Full-time

Re-posted 12 days ago


Job description

Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials.

We're looking for a Staff Data Engineer to lead the design, development, and operation of AI agents that power intelligent experiences across the Material Bank platform. This role sits at the intersection of data engineering, applied AI, and platform innovation, with the opportunity to shape how AI is embedded into the core of our business and customer experience. You'll be the technical lead defining how we build AI agents, with direct access to the teams interfacing with Snowflake with room to influence architecture decisions, and the chance to work across the full AI stack from data modeling and semantic layers to agent orchestration and production operations.

This is an exciting opportunity for someone who is, at their core, a passionate data engineer with deep curiosity about AI and significant experience building strong data foundations before expanding into applied AI and agent based systems. We are looking for someone who enjoys solving complex technical problems, experimenting with emerging technologies, and turning ambiguous ideas into scalable, production ready solutions. Working hands-on with Snowflake Cortex as our primary AI platform, you will help push the boundaries of what modern AI systems can do in an enterprise environment while helping define the future of intelligent experiences at Material Bank.

What You'll Do

  • Design, build, and operate production grade AI agents, owning the full lifecycle from prototyping and evaluation through deployment, monitoring, and continuous improvement.
  • Lead the development of scalable AI and data services, including MCP servers and REST APIs that expose intelligent capabilities to products, applications, and internal teams.
  • Serve as our internal expert on Snowflake Cortex, going deep on Cortex Agents, Cortex Analyst, and Cortex Search while partnering directly with Snowflake's account and product teams to influence capabilities and shape how we apply the platform.
  • Apply modern agent architecture patterns including RAG, tool use, orchestration, memory, and evaluation frameworks to build reliable, accurate, and cost efficient AI systems.
  • Partner closely with Analytics & Insights team to design and maintain semantic and metrics layers that create consistent business definitions across AI, analytics, and reporting use cases.
  • Build and maintain scalable data pipelines, transformations, and models that power AI workloads using Snowflake, dbt, and Airflow.
  • Collaborate across data, product, analytics, and engineering teams to translate ambiguous business problems into well designed AI and data solutions.
  • Establish engineering standards and best practices for agentic systems, including observability, evaluation, prompt management, governance, and operational guardrails.

What You'll bring:

  • Deep experience and genuine passion for data engineering, with strong instincts around data modeling, pipeline architecture, scalability, data quality, and building reliable platforms. Strong data foundations are core to this role.
  • 5+ years of experience in data engineering, AI/ML engineering, or related fields, including recent hands on experience building and shipping LLM powered applications or AI agents into production environments.
  • Experience building production APIs and services, including MCP servers and REST based architectures.
  • Strong understanding of modern agent development patterns including RAG, vector search, prompt engineering, tool/function calling, and frameworks such as LangChain, LangGraph, or LlamaIndex.
  • Deep expertise in Snowflake, including performance optimization, warehouse architecture, and scalable data modeling approaches such as dimensional modeling or Data Vault.
  • Production experience with dbt and Airflow, including building and maintaining semantic or metrics layers.
  • Strong Python engineering skills and solid experience working within AWS environments including services such as S3, IAM, Lambda, ECS, or similar.
  • Hands on experience using AI powered engineering tools such as Claude Code or similar development accelerators as part of real world engineering workflows.
  • Excitement about specializing deeply in Snowflake Cortex and helping define our long term AI platform strategy.

Nice to Have

  • Hands on experience working with Snowflake Cortex in production environments.
  • Experience with LLM evaluation, tracing, and observability platforms such as LangSmith, Arize, or Langfuse.
  • Experience partnering closely with analytics or BI teams to operationalize business metrics and semantic models.
  • Experience with Go, or a demonstrated ability to quickly learn and apply new technologies and programming languages.

What you'll get from us:

  • Our people: We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution.
  • Relaxation and Celebrations: Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect).
  • Health Benefits: We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program.
  • Plan for your Retirement: 401(k) eligible after your first 90 day's employed!
  • Giving Back: We sponsor multiple events throughout the year to help out our communities.
  • Growth: We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters!
  • Flexible Work Schedules: With business units and employees across the globe, Material Technologies has embraced a hybrid  working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both.

Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.