1

Tech Data Jobs in Seminole, FL (NOW HIRING)

STEMBoard is a technology solutions company that creates smart systems and software solutions for ... The Data Manager develops and governs data-oriented systems designed to meet the needs of an ...

The Data Scientist is primarily responsible for supporting/leading AI-driven initiatives that will ... Will be comfortable interacting at all levels of technology teams both internal and external to ...

Element has an opportunity for a Data Processor to join our rapidly expanding team. As a member of the operations team in one of the various laboratories across Element, the Data Processer position ...

Data Scientist Data Scientist Location: This role requires associates to be in-office 1-2 days per ... Creates presentations and seeks IT management approval and acceptance of significant replacements ...

In this role, you will apply data science, statistical analysis, automation, and emerging technologies to complex operational challenges within the information environment and irregular warfare (IW ...

The Data Science & Analytics Technical Lead will be responsible for : * Driving the strategic ... We integrate emerging technology, rapidly and securely, into mission critical operations that ...

Data Scientist Location: This role requires associates to be in-office 1-2 days per week, fostering ... Creates presentations and seeks IT management approval and acceptance of significant replacements ...

Data Architect

Tampa, FL · On-site

$60.25 - $77.50/hr

S. footprint that spans manufacturing, technology, and commercial operations across the country ... Data Architecture & Modeling * Design and maintain conceptual, logical, and physical data models ...

The Data Scientist is primarily responsible for supporting/leading AI-driven initiatives that will ... Will be comfortable interacting at all levels of technology teams both internal and external to ...

Showing results 41-60

Tech Data information

See Seminole, FL salary details

$10

$20

$30

How much do tech data jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for tech data in Seminole, FL is $20.19, according to ZipRecruiter salary data. Most workers in this role earn between $14.86 and $23.99 per hour, depending on experience, location, and employer.

What is a Tech Data specialist?

A Tech Data specialist is a professional who manages, analyzes, and interprets technical data to support business operations, decision-making, and IT systems. Their responsibilities often include data collection, data quality assurance, reporting, and collaborating with other departments to ensure accurate and secure data handling. Tech Data specialists may also work with databases, data warehouses, and analytics tools to extract insights and improve organizational efficiency. This role is vital in industries that rely on large volumes of technical or operational data.

What are the key skills and qualifications needed to thrive as a Tech Data analyst?

To thrive as a Tech Data Analyst, you need strong analytical skills, proficiency in data interpretation, and a background in statistics or computer science, often supported by a relevant degree. Familiarity with tools like SQL, Python, Excel, and data visualization platforms such as Tableau or Power BI, along with certifications in data analytics, is commonly required. Exceptional attention to detail, problem-solving ability, and effective communication are standout soft skills for this role. These skills and qualities are critical for transforming complex data into actionable insights that drive business decisions.

What are some common challenges faced by Tech Data professionals, and how can they be addressed?

Tech Data professionals often encounter challenges related to managing large volumes of complex data from diverse sources, ensuring data accuracy, and maintaining data security. To address these, it's important to implement robust data management tools, establish clear data governance protocols, and collaborate closely with IT and business teams. Continuous learning and staying updated on emerging technologies can also help professionals stay ahead of industry demands and overcome technical hurdles.

What is the difference between Tech Data vs Network Technician?

AspectTech DataNetwork Technician
Required CredentialsTypically requires a degree in IT, computer science, or related certifications like CompTIA A+ or Network+Often requires similar certifications, with emphasis on networking certifications like Cisco CCNA or CompTIA Network+
Work EnvironmentPrimarily in data centers, warehouses, or office settings managing hardware and software assetsPrimarily in office or on-site locations troubleshooting, installing, and maintaining network infrastructure
Employer & Industry UsageUsed by hardware suppliers, data centers, and IT service providersCommon in corporate IT departments, telecom companies, and managed service providers

Both roles require technical certifications and involve working with hardware and networks. Tech Data professionals focus on managing data assets and hardware logistics, while Network Technicians specialize in maintaining and troubleshooting network systems. The roles often overlap but differ mainly in scope and daily tasks.

What does tech data do?

A tech data professional typically manages and analyzes technology-related information, such as hardware, software, and network data, to support business operations. They often work with data management tools, databases, and may require knowledge of data analysis or IT systems to ensure accurate and efficient data handling.

What cities near Seminole, FL are hiring for Tech Data jobs?

Cities near Seminole, FL with the most Tech Data job openings:

Infographic showing various Tech Data job openings in Seminole, FL as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $44,125 per year, or $21.2 per hour.

Lead Forward Deployed Engineer, Microsoft AI & Data

Deloitte

Tampa, FL • On-site

$96K - $127K/yr

Full-time

Re-posted 27 days ago


Key responsibilities

  • Lead forward-deployed engineering pods that develop and deploy GenAI solutions into production for clients.

  • Serve as the senior client-facing engineering partner, building trusted relationships and leading discovery, success metric definition, and phased planning.

  • Lead and manage FDE pods, ensuring delivery standards, resource management, and coordination across multiple workstreams.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

47th of 154 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026

Work you'll do

As a Lead Microsoft AI&Data FDE, you will serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte's most strategic clients. You'll set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team. You'll translate engineering trade-offs into clear decisions for client leaders when needed. Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart. Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale.

Client Engagement

  • Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders
  • Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling
  • Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision
  • Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements-contributing to pipeline development and deal shaping.

Cross-Functional Pod Leadership & Program Governance

  • Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health
  • Enforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gates
  • Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.
  • Mentor and develop junior FDEs

GenAI Solution Development

  • Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below)
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls
  • Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid search-ensuring production-grade quality and scalability.
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.

Engineering & Data Foundations

  • Review and contribute to production-quality code
  • Guide architecture of data pipelines powering GenAI use cases
  • Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
  • Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud)


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $189,200 to $372,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026

Work you'll do

As a Lead Microsoft AI&Data FDE, you will serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte's most strategic clients. You'll set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team. You'll translate engineering trade-offs into clear decisions for client leaders when needed. Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart. Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale.

Client Engagement

  • Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders
  • Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling
  • Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision
  • Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements-contributing to pipeline development and deal shaping.

Cross-Functional Pod Leadership & Program Governance

  • Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health
  • Enforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gates
  • Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.
  • Mentor and develop junior FDEs

GenAI Solution Development

  • Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below)
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls
  • Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid search-ensuring production-grade quality and scalability.
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.

Engineering & Data Foundations

  • Review and contribute to production-quality code
  • Guide architecture of data pipelines powering GenAI use cases
  • Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
  • Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud)


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $189,200 to $372,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

What Deloitte employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom