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Data Conversion Jobs in Delaware (NOW HIRING)

Conversion Rate Optimization: * Identify areas of the user journey with conversion bottlenecks and ... Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ...

Conversion Rate Optimization: * Identify areas of the user journey with conversion bottlenecks and ... Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ...

Conversion Rate Optimization: * Identify areas of the user journey with conversion bottlenecks and ... Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ...

Conversion Rate Optimization: * Identify areas of the user journey with conversion bottlenecks and ... Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ...

Conversion Rate Optimization: * Identify areas of the user journey with conversion bottlenecks and ... Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ...

Conversion Rate Optimization: * Identify areas of the user journey with conversion bottlenecks and ... Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ...

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Showing results 1-20

Data Conversion information

See Delaware salary details

$11K

$110.1K

$139.6K

How much do data conversion jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data conversion in Delaware is $110,094.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,100.00 and $135,100.00 per year, depending on experience, location, and employer.

What is the data conversion role?

A data conversion role involves transforming data from one format or system to another to ensure compatibility, accuracy, and usability. It often requires knowledge of data management tools, scripting, and attention to detail to prevent data loss or errors during the process.

What data jobs pay the most?

Data-related roles such as Data Scientist, Data Engineer, and Machine Learning Engineer tend to have the highest salaries in the data field, often exceeding six figures annually. These positions typically require strong technical skills, experience with programming languages like Python or SQL, and advanced education or certifications. Salary levels can vary based on industry, location, and experience.

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

To thrive in a Data Conversion role, you need strong attention to detail, data analysis skills, and experience with database management or programming, often supported by a relevant degree or certifications in IT or computer science. Familiarity with data manipulation tools such as SQL, ETL software, and various file formats is typically required. Strong problem-solving abilities, effective communication, and adaptability are valuable soft skills for this position. These skills help ensure accurate and efficient transformation of data between systems, which is critical for smooth business operations and data integrity.

Do data entry jobs really pay?

Data entry jobs typically pay hourly wages that can range from minimum wage to higher rates depending on experience, complexity of tasks, and employer. Pay rates vary widely, with some positions offering part-time or freelance opportunities, and skills in software like Excel or data management tools can influence earning potential.

What are some common challenges faced in a Data Conversion role, and how are they typically addressed?

One of the most common challenges in Data Conversion is managing data inconsistencies and ensuring data quality during large-scale migrations or system upgrades. Professionals in this field often work closely with IT teams, business analysts, and end-users to identify and resolve data discrepancies or mapping issues. Effective troubleshooting, thorough testing, and clear documentation are standard practices to address these challenges. Communication skills and a proactive approach greatly help in anticipating issues and minimizing downtime during critical data transitions.

What is a Data Conversion job?

A Data Conversion job involves transforming data from one format, structure, or system to another while ensuring accuracy and consistency. This process is common when migrating data between software systems, upgrading databases, or integrating new technologies. Professionals in this role use specialized tools and scripts to clean, map, and validate data. Their goal is to prevent data loss, maintain data integrity, and ensure seamless usability in the new system.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst, as the role values skills in data analysis, programming, and tools like Excel, SQL, and Python. Many professionals transition into data analysis later in their careers by gaining relevant certifications and experience, regardless of age.
What are popular job titles related to Data Conversion jobs in Delaware? For Data Conversion jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Data Conversion jobs in Delaware look for? The top searched job categories for Data Conversion jobs in Delaware are:
Power BI Architect - DE/Wilmington - Onsite work Locals only needed

Power BI Architect - DE/Wilmington - Onsite work Locals only needed

Vinsari LLC

Wilmington, DE โ€ข On-site

$61.75 - $79.50/hr

Other

Posted 5 days ago


Job description

Power BI Architect - DE/Wilmington - Onsite work Locals only needed

Requisition Name: Power BI Architect

Start Date: 7/13/2026

Duration: 24 Weeks

Services Location: DE/Wilmington

Max Rate: 63 $ phr on W2 or 70 $ phr on Corp- Corp all inc

Description Of Services:
Must Have Technical/Functional Skills:

  • 10+ years in data/solution architecture with strong ownership of enterprise-scale implementations.
  • Strong experience designing data warehouses/lake houses, enterprise integration, and analytics platforms.
  • Strong in data modeling (dimensional + normalized) and semantic layer design.
  • Strong understanding of business processes and data:

Commercial operations , Logistics: shipment tracking, carrier costs, delivery performance

procurement, inventory, logistics, supplier management, costing

  • Cloud & Data Tech Stack (choose based on your environment)
  • Cloud: Azure
  • Data platforms: Fabric / Synapse
  • Data integration: Informatica / ADF / Fivetran / dbt / Airflow (any relevant)
  • Storage & formats: Parquet/Delta/Iceberg; S3/ADLSS
  • Querying: advanced SQL; performance tuning; data partition strategies
  • Data governance: Collibra / Purview / Alation (or equivalent)
  • BI/Analytics: Power BI (data modeling, DAX, performance tuning, semantic layer design, governance, deployment pipelines)
  • This role requires strong data architecture, data modeling, integration design, governance, and hands-on experience with modern cloud data platforms and analytics.
  • Design semantic models in Power BI for enterprise-wide reuse, ensuring consistent KPI definitions.
  • Hands-on experience in DAX optimization, performance tuning, composite models, and security (RLS/OLS).
  • Implement workspace architecture, deployment pipelines, and governance best practices in Power BI.
  • Experience with real-time analytics, event streams, and near real-time dashboards for operational insights.

Roles & Responsibilities:

  • Masters in PowerBI, Finance Solution Data Architect with deep expertise in Supply Chain data and its intersection with Finance (Procure-to-Pay, Inventory Accounting, Costing, CapEx/OpEx, Vendor Spend Analytics).
  • The architect will lead the design of scalable data solutions that unify supply chain and finance data across ERP, procurement, logistics, inventory, and billing systems enabling accurate reporting, forecasting, compliance, and operational insights.

Data Architecture & Solution Design

  • Own end-to-end data architecture for finance + supply chain analytics, reporting, and operational use-cases.
  • Define target-state architecture (lake house/warehouse, streaming, APIs, metadata) aligned to enterprise standards.
  • Design robust data ingestion and integration patterns (batch/stream, CDC, API-based, file-based).
  • Ensure architecture supports auditability, reconciliation, and financial controls (traceability from source to report).

2) Supply Chain + Finance Domain Alignment

  • Architect domain-aligned datasets for:
  • Procure-to-Pay (P2P): requisitions, purchase orders, invoices, payments
  • Inventory & Warehousing: receipts, transfers, adjustments, stock valuation
  • Costing: standard/actual costing, landed cost, freight, BOM where relevant
  • Vendor & Spend: vendor master, contracts, pricing, spend categorization
  • Logistics: shipment tracking, carrier costs, delivery performance
  • Enable integration between supply chain events and finance outcomes (e.g., GR/IR, accruals, capitalization, write-offs).

3) Data Modeling & Semantics

  • Create and maintain conceptual, logical, and physical data models (3NF, dimensional, Data Vault as applicable).
  • Define canonical models and enterprise semantic layers for KPI consistency.
  • Establish best practices for:
  • Master data (vendors, materials/items, locations, cost centers)
  • Reference data (currency, UOM, fiscal calendar, shipping terms)
  • Hierarchies (product, supplier, org, region)

5) Platform & Engineering Collaboration

  • Partner with data engineering teams to implement:
  • ETL/ELT pipelines, orchestration, CI/CD, environment management
  • Performance tuning, partitioning, indexing, clustering strategies
  • Observability (logging, monitoring, SLA/SLI, cost optimization)
  • Enable governed self-service analytics through reusable datasets and thin-report architecture.

Generic Managerial Skills, If any

  • Stakeholder Management & Delivery
  • Engage Finance, Supply Chain, Procurement, and IT stakeholders to translate needs into architecture.
  • Lead architecture reviews, technical documentation, and implementation roadmaps.
  • Work with program/product managers to define scope, milestones, dependencies, and risk mitigation
  • Education
  • Bachelor of Engineering/Computers

Deliverables:
-Process Flows -Mentor and Knowledge transfer to client project team members -Participate as primary, co and/or contributing author on any and all project deliverables associated with their assigned areas of responsibility -Participate in data conversion and data maintenance -Provide best practice and industry specific solutions -Advise on and provide alternative (out of the box) solutions -Provide thought leadership as well as hands on technical configuration/development as needed. -Participate as a team member of the functional team -Perform other duties as assigned.