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Data Modeling Jobs in Delaware (NOW HIRING)

Purple Drive Technologies

Data Architect

Wilmington, DE · On-site

$61.75 - $79.50/hr

Proficiency in SQL, relational databases (Oracle, SQL Server, DB2), and data modeling. Credit Card Systems: Familiarity with major credit card processing platforms (e.g., TSYS, FIS, First Data, etc.

Barclays

AVP, Quantitative Modeler

Wilmington, DE

$53.25 - $69/hr

Engage in complex analysis of data from multiple sources of information, internal and external ... Utilize Python/SAS and robust modeling conceptual frameworks to perform quantitative model ...

Bridgeforce

Data Engineer

Wilmington, DE

The duties of this role range from data modeling and database development to building and maintaining reliable, efficient data routines that support analytics and the company's products. It is ...

Bridgeforce

Data Engineer

Wilmington, DE

$78K - $117K/yr

The duties of this role range from data modeling and database development to building and maintaining reliable, efficient data routines that support analytics and the company's products. It is ...

Pbf Energy

Data and Insights Architect

Delaware City, DE

$121.16K - $216.09K/yr

Data Modeling & Governance * Develop and maintain conceptual, logical, and physical data models * Ensure compliance with governance, privacy, and regulatory standards * Innovation & Knowledge Sharing

Dlapiper

Data Engineer

Wilmington, DE

$111.10K - $133.40K/yr

Collaboration & Delivery (Agile Pod Model) * Work cross-functionally with engineers, analysts, and stakeholders to understand requirements and deliver data solutions that support sprint-based ...

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How much do data modeling jobs pay per hour?

As of May 31, 2026, the average hourly pay for data modeling in Delaware is $58.76, according to ZipRecruiter salary data. Most workers in this role earn between $52.69 and $68.32 per hour, depending on experience, location, and employer.

What is a Data Modeling job?

A Data Modeling job involves designing and structuring data to ensure it is organized, efficient, and scalable for business needs. Data modelers create conceptual, logical, and physical data models that define relationships between data elements. They work closely with database administrators, data engineers, and analysts to optimize data storage and retrieval. Their role is crucial for maintaining data integrity and supporting business intelligence and analytics initiatives. Skills in SQL, database design, and data normalization are essential for success in this role.

What are the key skills and qualifications needed to thrive in the Data Modeling position, and why are they important?

To thrive in Data Modeling, you need strong analytical skills, proficiency in database design, and a solid understanding of data structures, usually supported by a degree in computer science, information systems, or a related field. Expertise with tools such as ERwin, SQL, PowerDesigner, or similar data modeling software, as well as knowledge of normalization techniques and experience with data warehousing concepts, are highly valued. Effective communication, attention to detail, and problem-solving abilities set outstanding data modelers apart, allowing them to convey complex concepts to both technical and non-technical stakeholders. These skills are vital for building accurate, scalable data models that serve as the foundation for reliable data-driven decision-making within organizations.

What does a typical day look like for someone working in Data Modeling?

A typical day in Data Modeling often involves collaborating with business analysts, database administrators, and software developers to understand data requirements and translate them into logical and physical data structures. Data modelers spend time designing, reviewing, and optimizing data models, ensuring accuracy and consistency across systems and projects. They also review data flows, document data dictionaries, and participate in meetings to align data architecture with overall business needs. The role frequently requires balancing independent technical work with teamwork, as well as responding to feedback and evolving project requirements to support organizational goals.

What are the four types of data modeling?

Data modeling in data analysis and database design typically includes four main types: conceptual, logical, physical, and dimensional modeling. Conceptual models define high-level data structures, logical models specify detailed structures without physical considerations, physical models translate logical models into actual database schemas, and dimensional models are used in data warehousing for analytical purposes. Data modelers often use tools like ER diagrams and require understanding of database systems and business requirements.
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What are popular job titles related to Data Modeling jobs in Delaware? For Data Modeling jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Data Modeling jobs in Delaware look for? The top searched job categories for Data Modeling jobs in Delaware are:
What cities in Delaware are hiring for Data Modeling jobs? Cities in Delaware with the most Data Modeling job openings:
Data Modeling jobs near you
Infographic showing various Data Modeling job openings in Delaware as of May 2026, with employment types broken down into 2% Internship, 75% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $122,228 per year, or $58.8 per hour.

Data Architect

Purple Drive Technologies

Wilmington, DE • On-site

$61.75 - $79.50/hr

Full-time

Posted 27 days ago

Job description

Overview:
Data Architect:
Technical Skills
Data Mapping & Migration: Experience with data mapping, data migration, and ETL (Extract, Transform, Load) processes.
Database Knowledge: Proficiency in SQL, relational databases (Oracle, SQL Server, DB2), and data modeling.
Credit Card Systems: Familiarity with major credit card processing platforms (e.g., TSYS, FIS, First Data, etc.).
Data Quality & Validation: Skills in data validation, cleansing, and reconciliation.
Business & Domain Knowledge
Credit Card Operations: Understanding of credit card lifecycle, transaction processing, account management, and compliance (PCI DSS).
Regulatory Requirements: Awareness of financial regulations and data privacy laws relevant to credit card data.
Project Management & Analytical Skills
Requirements Gathering: Ability to work with business analysts and stakeholders to gather and document data mapping requirements.
Problem Solving: Strong analytical and troubleshooting skills for resolving data discrepancies.
Documentation: Experience in creating detailed mapping documents, data dictionaries, and conversion plans.
Soft Skills
Communication: Excellent verbal and written communication skills for collaborating with cross-functional teams.
Attention to Detail: High level of accuracy and attention to detail in data mapping and validation.
Teamwork: Ability to work effectively in project teams, often under tight deadlines.
Roles & Responsibilities
The Credit Card Systems Conversion Data Mapping Specialist is responsible for analyzing, mapping, and migrating data between legacy and new credit card processing systems. This role ensures the integrity, accuracy, and completeness of data throughout the conversion process, working closely with business stakeholders, IT teams, and vendors.
Key Responsibilities
Analyze existing credit card system data structures and identify mapping requirements for conversion to new platforms.
Develop detailed data mapping documentation, including source-to-target mapping, transformation rules, and data dictionaries.
Collaborate with business analysts, system owners, and technical teams to gather requirements and validate mapping logic.
Design and execute data migration and ETL processes, ensuring data quality, consistency, and compliance with regulatory standards.
Perform data validation, reconciliation, and troubleshooting to resolve discrepancies during conversion.
Support testing activities, including unit, system integration, and user acceptance testing, by providing test data and validating results.
Document conversion processes, mapping logic, and any issues encountered for future reference and audit purposes.
Ensure compliance with PCI DSS and other relevant data privacy and security regulations.
Provide post-conversion support, including data issue resolution and process optimization.

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