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Associate Data Engineer Jobs in Jacksonville, FL

... Associate, Snowflake Core, Snowflake Architect, Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies - Developing and documenting data ...

Data Strategy-Manager

Jacksonville, FL · On-site

$99K - $232K/yr

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in ...

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary ...

Azure Solutions Architect Expert, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Proficient in Python and SQL - Experience with Docker and ...

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer/Data Analyst/ML - Proven leadership in data-driven strategies - Demonstrating ...

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Associate Data Engineer information

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How much do associate data engineer jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for associate data engineer in Jacksonville, FL is $17.36, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $18.51 per hour, depending on experience, location, and employer.

What does an associate data engineer do?

An Associate Data Engineer is responsible for supporting the development, maintenance, and optimization of data pipelines and databases. They work closely with senior data engineers and other IT professionals to ensure data is accessible, reliable, and efficiently processed for analytics and business use. Typical tasks include writing and testing code for data integration, troubleshooting data issues, and implementing data security best practices. This entry-level position is a foundational role that builds technical skills and experience in data engineering.

What are the key skills and qualifications needed to thrive as an associate data engineer?

To thrive as an Associate Data Engineer, you need a solid understanding of data modeling, SQL, Python, and foundational knowledge of database concepts, often backed by a degree in computer science or a related field. Familiarity with data warehousing tools (like AWS Redshift, Google BigQuery), ETL frameworks, and cloud platforms as well as industry certifications such as AWS Certified Data Analytics is beneficial. Strong problem-solving skills, attention to detail, and effective communication help you navigate complex data challenges and collaborate with teams. These abilities are crucial for ensuring data systems are reliable, scalable, and aligned with organizational goals.

What are some common challenges an associate data engineer may face when working with large-scale data pipelines?

As an Associate Data Engineer, you may often encounter challenges such as optimizing data pipeline performance, ensuring data quality, and troubleshooting bottlenecks when processing large volumes of data. Working with distributed systems can introduce complex issues like latency and data consistency. Collaborating effectively with data scientists, analysts, and senior engineers is crucial for aligning data infrastructure with evolving project requirements. Regularly learning new tools and best practices will help you adapt to these challenges and grow in your role.

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

AspectAssociate Data EngineerData Engineer
Required CredentialsBachelor's degree in CS, Data Science, or related field; basic knowledge of SQL and PythonBachelor's or Master's degree; advanced knowledge of SQL, Python, Spark, and cloud platforms
Work EnvironmentEntry-level, team-focused, often in tech or finance industriesMid to senior level, designing and maintaining data pipelines in various industries
Employer & Industry UsageCommon in tech companies, startups, and finance firmsUsed across industries for building scalable data infrastructure
Common Search & ComparisonOften compared for career progression and skill requirements

The Associate Data Engineer role is an entry-level position focusing on supporting data infrastructure, while the Data Engineer is a more advanced role responsible for designing and maintaining complex data systems. The roles share similar educational backgrounds and work environments but differ in experience level and responsibilities.

Is an associate data engineer entry level?

An associate data engineer is typically an entry-level position suitable for candidates with limited professional experience in data engineering. It often requires foundational skills in SQL, Python, or cloud platforms and serves as a starting point for a career in data engineering.

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

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

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

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

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

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

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

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

Infographic showing various Associate Data Engineer job openings in Jacksonville, FL as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $36,112 per year, or $17.4 per hour.

Associate Data Scientist

Jacksonville, FL • On-site

Intercontinental Exchange Holdings, Inc.
Finance and Insurance • 5 - 10K employees

$70 - $90/hr

Other

Re-posted 3 days ago


Job description

Overview

US Citizens only

Please note that pursuant to a government contract, this specific position requires U.S. citizen, U.S. national or protected individual (as defined in 8 U.S.C. § 1324b(a)(3)) status.

Job Purpose

Intercontinental Exchange is seeking a Data Scientist I to join our Loan Data team. As a Data Scientist I, you will play a critical role in analyzing complex loan data sets to identify trends, develop data products, and drive business insights that inform our clients' investment decisions and business strategies. You will work closely with our team to design, develop, and implement data-driven solutions that meet the evolving needs of our clients and drive growth in the loan market.

Responsibilities
  • Loan Data Analysis:
    • Collect, process, and analyze large loan data sets from various sources (e.g., loan origination systems, servicing platforms).
    • Identify trends, patterns, and anomalies in loan data using statistical techniques and data visualization tools.
    • Develop and maintain databases and data systems to support loan data analysis and modeling.
  • Data Quality & Data Stewardship:
    • Monitor and assess the quality of loan data across internal and external sources.
    • Identify data quality issues, anomalies, and inconsistencies through analysis and validation checks.
    • Partner with data providers, clients, developers, and stakeholders to investigate root causes and drive issue remediation.
    • Contribute to the development of data quality rules, monitoring processes, and controls.
    • Document data quality issues and track resolution progress.
  • Insight Generation:
    • Communicate complex loan data insights and model results to non-technical stakeholders.
    • Develop and present reports, dashboards, and visualizations to support business decisions.
    • Collaborate with stakeholders to identify business problems and develop data-driven solutions.
  • Data Engineering:
    • Design, develop, and maintain data pipelines and architectures to support loan data analysis and modeling.
    • Collaborate with data engineers to implement data solutions and integrate with existing systems.
  • Research and Development:
    • Stay up-to-date with industry trends, research, and developments in data science, machine learning, and related fields.
    • Explore new technologies, tools, and methodologies to enhance existing loan data solutions and models.
Knowledge and Experience
  • Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.
  • Proficiency in programming languages (e.g., Python, R, SQL) and software tools (e.g., pandas, NumPy, scikit-learn).
  • Experience with loan data analysis, machine learning, and data visualization.
  • Familiarity with relational database tools and environments such as SSMS, along with exposure to modern data platforms such as Databricks or Snowflake.
  • Experience with AI-assisted development and analytics tools and ability to incorporate them into data analysis and workflow processes.
  • Strong analytical and problem-solving skills, with the ability to analyze complex loan data sets and develop creative solutions.
  • Experience with data visualization tools (e.g., Sigma, Tableau, Power BI).
  • Excellent communication and collaboration skills, with the ability to work effectively with technical and non-technical stakeholders.
Nice to Have
  • Advanced Degree:
    • Master's or Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related field.
  • Certifications:
    • Certified Data Scientist (CDS), Certified Analytics Professional (CAP), or other relevant certifications.
  • Cloud Computing:
    • Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud, Snowflake).
  • Domain Expertise:
    • Familiarity with loan markets, loan products, and lending regulations.

Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.

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