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Data Engineer Jobs in Melbourne, FL (NOW HIRING)

Python, R, or similar programming languages * Machine learning frameworks (scikit-learn, TensorFlow, PyTorch) * Statistical analysis and modeling * Data visualization tools (Matplotlib, Seaborn ...

Associate, Data Architect

Melbourne, FL ยท On-site

$74K - $138K/yr

... with Data Engineers and team members to understand data sources, structures, and pipelines that feed BI solutions Identify opportunities to automate manual processes and workflows using Power ...

New

Melbourne, FL L3Harris Enterprise Data and AI team is seeking a Data Engineer with experience in managing enterprise-level data life cycle processes. This role includes overseeing data ETL/ELT ...

New

Melbourne, FL L3Harris Enterprise Data and AI team is seeking a Data Engineer with experience in managing enterprise-level data life cycle processes. This role includes overseeing data ETL/ELT ...

New

Develop and maintain data processing applications primarily in Java, ensuring high performance, reliability, and security for mission-critical systems. * Design and manage NoSQL databases ...

Senior Associate, Data Architect

Melbourne, FL ยท On-site

$84K - $156K/yr

... with Data Engineers and team members to understand data sources, structures, and pipelines that feed BI solutions Identify opportunities to automate manual processes and workflows using Power ...

New

Showing results 21-40

Data Engineer information

See Melbourne, FL salary details

$41.2K

$120.2K

$164.5K

How much do data engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for data engineer in Melbourne, FL is $120,237.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $127,500.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

What are the key skills and qualifications needed to thrive as a data engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.

What are the most commonly searched types of Data Engineer jobs in Melbourne, FL?

The most popular types of Data Engineer jobs in Melbourne, FL are:

What are popular job titles related to Data Engineer jobs in Melbourne, FL?

For Data Engineer jobs in Melbourne, FL, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Melbourne, FL look for?

The top searched job categories for Data Engineer jobs in Melbourne, FL are:

What cities near Melbourne, FL are hiring for Data Engineer jobs?

Cities near Melbourne, FL with the most Data Engineer job openings:

Infographic showing various Data Engineer job openings in Melbourne, FL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $120,237 per year, or $57.8 per hour.

Data Scientist

kgs

Cape Canaveral, FL โ€ข On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 19 days ago


Job description

Koniag IT Systems, LLC, a Koniag Government Services company, is seeking a Data Scientist with a Secret security clearance to support KITS and our government customer at Stennis Space Center, MS.

We offer competitive compensation and an extraordinary benefits package including health, dental and vision insurance, 401K with company matching, flexible spending accounts, paid holidays, three weeks paid time off, and more.

Koniag IT Systems, LLC, a Koniag Government Services company, is seeking a skilled Data Scientist to join our team at Stennis Space Center, Mississippi. The ideal candidate will leverage advanced analytics, machine learning, and geospatial analysis techniques to extract valuable insights from complex datasets. This position offers the opportunity to work with cutting-edge technologies and contribute to mission-critical projects while solving challenging analytical problems.

The Data Scientist will be responsible for developing and implementing advanced analytical solutions, with a particular focus on geospatial data analysis and modeling.

Key responsibilities include:

  • Design and implement machine learning models and statistical analyses
  • Develop predictive models and data-driven solutions
  • Process and analyze large-scale geospatial datasets
  • Create data visualization and reporting solutions
  • Conduct exploratory data analysis
  • Develop and maintain analytical pipelines
  • Collaborate with cross-functional teams to understand requirements
  • Transform complex data into actionable insights
  • Optimize existing models and analytical processes
  • Document methodologies and findings
  • Present technical findings to stakeholders

Education and Experience:

  • Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field
  • 5+ years of experience in data science or related field
  • Proven experience with machine learning and statistical modeling
  • Strong background in geospatial analysis
  • Demonstrated track record of successful analytical projects

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Required Skills and Competencies:

  • Python, R, or similar programming languages
  • Machine learning frameworks (scikit-learn, TensorFlow, PyTorch)
  • Statistical analysis and modeling
  • Data visualization tools (Matplotlib, Seaborn, Plotly)
  • SQL and database querying
  • Geographic Information Systems (GIS), specifically: Commercial Joint Mapping Toolkit (CJMTK)
  • ESRI ArcGIS suite of commercial software components
  • ArcGIS Runtime
  • ArcGIS Engine
  • ArcGIS extensions including: 3-D Analyst
  • Geostatistical Analyst
  • Network Analyst
  • Spatial Analyst
  • Tracking Analyst
  • ArcGIS Server
  • Experience with:
  • Spatial statistics and analysis
  • Big data processing tools
  • Version control systems (Git)
  • Jupyter notebooks
  • Data preprocessing and feature engineering
  • Model evaluation and validation techniques
  • Strong analytical and problem-solving skills
  • Excellent communication abilities
  • Must be able to work on-site at Stennis Space Center, MS

Clearance Requirement:

  • Secret security clearanceย 

Desired Skills and Competencies:

  • Deep learning techniques
  • Computer vision
  • Natural language processing
  • Cloud computing platforms (AWS, Azure, GCP)
  • Big data technologies (Hadoop, Spark)
  • Remote sensing data analysis
  • Time series analysis
  • Spatial modeling
  • Bayesian statistics
  • Knowledge of:
  • Data engineering principles
  • MLOps practices
  • Distributed computing
  • High-performance computing
  • Image processing
  • Familiarity with:
  • Federal data standards
  • Research methodology
  • Scientific computing
  • Geospatial data formats and standards
  • Publications in peer-reviewed journals
  • Federal government contract experience
  • Security clearance or ability to obtain one
  • Relevant certifications in data science or machine learning

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Our Equal Employment Opportunity Policy

The company is an equal opportunity employer. The company shall not discriminate against any employee or applicant because of race, color, religion, creed, ethnicity, sex, sexual orientation, gender or gender identity (except where gender is a bona fide occupational qualification), national origin or ancestry, age, disability, citizenship, military/veteran status, marital status, genetic information or any other characteristic protected by applicable federal, state, or local law. We are committed to equal employment opportunity in all decisions related to employment, promotion, wages, benefits, and all other privileges, terms, and conditions of employment.

The company is dedicated to seeking all qualified applicants. If you require an accommodation to navigate or apply for a position on our website, please get in touch with Heaven Wood via e-mail atย accommodations@koniag-gs.comย or by calling 703-488-9377 to request accommodations.

Koniag Government Services (KGS) is an Alaska Native Owned corporation supporting the values and traditions of our native communities through an agile employee and corporate culture that delivers Enterprise Solutions, Professional Services and Operational Management to Federal Government Agencies. As a wholly owned subsidiary of Koniag, we apply our proven commercial solutions to a deep knowledge of Defense and Civilian missions to provide forward leaning technical, professional, and operational solutions. KGS enables successful mission outcomes for our customers through solution-oriented business partnerships and a commitment to exceptional service delivery. We ensure long-term success with a continuous improvement approach while balancing the collective interests of our customers, employees, and native communities. For more information, please visitย www.koniag-gs.com.

Equal Opportunity Employer/Veterans/Disabled.ย Shareholder Preference in accordance with Public Law 88-352