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Data Ops Engineer Jobs in Florida (NOW HIRING)

NTT DATA Services

Senior Data Scientist

Tampa, FL · On-site +1

NTT is seeking a Data Scientist / ML engineer with 7+ years of experience. This person should be ... AI/ML o ML Ops 7+ years of experience using Python and/or R to analyze disparate datasets.

NTT DATA Services

Senior Data Scientist

Tampa, FL · On-site +1

NTT is seeking a Data Scientist / ML engineer with 7+ years of experience. This person should be ... ML o ML Ops • 7+ years of experience using Python and/or R to analyze disparate datasets.

NTT DATA Services

Senior Data Scientist

Tampa, FL · On-site

NTT is seeking a Data Scientist / ML engineer with 7+ years of experience. This person should be ... ML o ML Ops • 7+ years of experience using Python and/or R to analyze disparate datasets.

University of Florida

OPS Lab Manager

Gainesville, FL · On-site

$17 - $25/hr

Curation of laboratory data and biological material * This position includes operating laboratory ... Preferred: * Has background or experience related in bioengineering or mechanical engineering.

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Data Ops Engineer information

See Florida salary details

$33.3K

$96.9K

$132.6K

How much do data ops engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for data ops engineer in Florida is $96,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,600.00 and $102,800.00 per year, depending on experience, location, and employer.

What are Data Ops Engineers?

Data Ops Engineers are professionals who bridge the gap between data engineering and operations. They focus on automating, monitoring, and optimizing data pipelines to ensure reliable, efficient, and secure data flow within organizations. Their responsibilities often include managing data integration, workflow orchestration, deployment of data infrastructure, and implementing best practices for data quality and governance. Data Ops Engineers work closely with data scientists, analysts, and IT teams to support data-driven decision-making and maintain high data availability. Their role is crucial in modern organizations that rely on large-scale data processing and analytics.

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

To thrive as a Data Ops Engineer, you need a solid background in data engineering, automation, and cloud infrastructure, often supported by a degree in computer science or related field. Experience with tools like Apache Airflow, Docker, Kubernetes, CI/CD pipelines, and proficiency in scripting languages such as Python or Bash is typically required. Strong problem-solving skills, attention to detail, and effective communication help you collaborate with data teams and troubleshoot complex data workflows. These skills ensure reliable data delivery, streamlined operations, and scalable solutions that support organizational data goals.

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

AspectData Ops EngineerData Engineer
CredentialsCertifications in data management, cloud platforms, scriptingCertifications in data engineering, SQL, cloud services
Work EnvironmentFocus on data pipelines, automation, deployment, and monitoringFocus on data modeling, ETL processes, database design
Industry UsageUsed in organizations emphasizing data operations, automation, and DevOps practicesUsed in data-centric roles focusing on building data infrastructure

While both roles work with data infrastructure, Data Ops Engineers primarily focus on automating and managing data pipelines and deployment processes, whereas Data Engineers concentrate on designing and building data systems. The roles often overlap but differ in their core focus areas and responsibilities.

How does a Data Ops Engineer typically collaborate with data scientists and software engineers within an organization?

Data Ops Engineers play a crucial role in bridging the gap between data science and engineering teams. They ensure smooth data pipeline operations, help automate workflows, and support data scientists by providing reliable, scalable infrastructure. Collaboration often involves participating in cross-functional meetings to understand data requirements, troubleshooting data quality issues, and implementing solutions that enable efficient experimentation and model deployment. This collaborative environment helps facilitate quick iterations and reliable delivery of data products.
What are popular job titles related to Data Ops Engineer jobs in Florida? For Data Ops Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Data Ops Engineer jobs in Florida look for? The top searched job categories for Data Ops Engineer jobs in Florida are:
Data Ops Engineer jobs near you
Infographic showing various Data Ops Engineer job openings in Florida as of June 2026, with employment types broken down into 2% As Needed, 61% Full Time, 36% Part Time, and 1% Temporary. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $96,936 per year, or $46.6 per hour.
Sr. Data Engineer

Sr. Data Engineer

Symbiotic Consulting Group

Deerfield Beach, FL

$110K - $133K/yr

Other

Posted 12 days ago

Job description

Sr. Data Engineer will be responsible for developing curated data (data models, data ETL pipelines, views) in a cloud-based environment to support business needs for analytics and reporting. The engineer will assist an existing team with migration from on prem to cloud-based data delivery platform and should have experience in migration of environments.  The candidate will provide guidance and support for the set-up of the new environment along with best practices and recommendations based on industry and hands on experience as a data engineer. In addition, the candidate should have experience with standardizing data modeling and design frameworks for analysis, design, building, testing and maintenance.  Cloud based data engineering is required and experience using the Azure stack is highly preferred and recommended.  Candidates must possess the technical capabilities to extract, retrieve and analyze data with SQL based tools. The engineer should possess strong interpersonal communication skills to be able to bridge the gap between business and technical users to understand and assess requirements and deliver data driven solutions. The role will also involve adhering to data governance standards and practices along with experience developing in an agile environment using Azure boards or similar tool such as Azure Dev Ops.

       Responsible for eliciting, understanding, interpreting and representing business requirements.

       Act as the conduit between the customer and technical teams to ensure requirements are understood.

       Responsible for understanding business processes to develop business models.

       Provide subject matter expertise on the use of data as well as educate teams on business model, metadata and standards.

       Responsible for understanding source systems and its data models.

       Develop source to target mappings for data lineage.

       Document source architecture to include data flows.

       Responsible for analyzing data to validate business domains and requirements.

       Responsible for data profiling and ensuring data quality requirements are accurate and complete.

       Act in an advisory capacity in data model reviews, architecture approach and solution design to ensure high quality deliverables.

       Responsible for partnering with management and business units on innovative ways to successfully utilize data and related tools to advance business objectives.

       Responsible for providing day-to-day support, troubleshooting and incident management and resolution.

       Responsible for communicating planned and unplanned activities to appropriate parties as needed.

       Provide ad hoc support for Business reporting requests

Requirements

       Bachelor’s degree or equivalent plus 7 years of related professional experience. Degree in technology related area preferred.

       5+ years experience as a Data Engineer/Analyst, specifically utilizing Azure Data & Analytics PaaS Services (Azure Data Factory, Azure Data Lake, Azure SQL DW)

       5+ Experience with JSON

       5+ years hands-on experience working with SQL.

       5+ years experience with data modeling concepts and techniques.

       5+ years experience of hands-on with Informatica Power Center and IICS development

       Strong experience building data pipelines to bring together information from different source systems.

       Strong NoSQL experience with CosmosDB

       Experience working with Microsoft Power Platform (PowerBi, PowerApps, PowerAutomate) a plus

       Well versed in data management concepts, data lifecycle and methodologies.

       Must exhibit strong thought leadership.

       Skillful at applying business and technical skills to drive innovation and performance improvement.

       Excellent analytical, problem-solving, and decision-making skills, leveraging both logic and creativity.

       Excellent written and oral communication, as well as, good organizational and presentation skills.

       Demonstrated ability to handle multiple competing priorities in a dynamic environment.

       Demonstrated facilitation and meeting management skills.

       Demonstrated ability to understand the unique needs of the customer and translate to actionable results while delivering high quality outcomes.

       Ability to influence and motivate individuals and teams to drive mutually beneficial outcomes.

       Excellent interpersonal skills with the ability to build relationships within and between individuals and cross-functional teams.

       Must enjoy working in a team-oriented, collaborative environment as well as autonomously.

       High achievement orientation with a willingness to learn.

       Possess a solid overall understanding of technology concepts, trends, and capabilities.

       Exhibit a strong desire to understand the organization, its industry, and its strategies.

       Working knowledge of project management principles, a plus.

       Must exhibit strong customer service orientation.

       Must be willing to be on-call as needed.

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