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Overview
At World Business Lenders (WBL), we provide flexible, short-term commercial loans backed by real estate to help small and medium-sized businesses across the United States, particularly those facing difficulties with traditional financing.
This position is a Contract/Consultant role with working hours typically from 9:00 am-6:00 pm Eastern Standard Time, Monday through Friday. Applicants should have an excellent command of the English language, both spoken and written.
We request that you submit your CV in English.
Job Duties and Responsibilities
Improved data pipelines (via automation) with quality checks to ensure data accuracy, consistency, and reliability throughout the entire data processing workflow, reducing manual intervention and minimizing errors.
Migration of legacy systems to new systems, involving thorough analysis, seamless data transfer, and integration to enhance system performance and maintain continuity without disrupting existing operations.
Requirements
Role Requirements
Education:
A Bachelor’s degree Computer Science, Engineering, Information Systems, or a related field is preferred — but we also highly value equivalent hands-on experience.
Experience:
4 to 7 years of experience as a Data Engineer.
We value practical, hands-on expertise that goes beyond just theoretical knowledge.
Required Background / Industry Experience
Experience working with cloud-based data platforms and environments
Strong SQL skills with data modeling experience for data warehouses
Strong Python skills (especially notebooks) for building and maintaining data workflows
Experience developing and maintaining ETL/ELT processes
Experience working with data warehouses used by reporting/business teams
Experience using Git/GitHub for version control in collaborative environments
Understanding of data engineering best practices:
Pipeline orchestration and dependency management
Data quality, validation, and monitoring fundamentals
Required for migration-focused role
Hands-on data migration experience:
Schema mapping and transformation
Data reconciliation and validation (must be strong here)
Data quality checks, integrity validation, and issue resolution
Backfills and historical data handling
Cutover planning and execution
Required for automation-focused role
Experience building and maintaining automated data pipelines:
Scheduling, orchestration, and failure handling
Workflow reliability, monitoring, and repeatability
Preferred
Experience within Microsoft Fabric or broader Microsoft Azure data ecosystem
Experience with orchestration tools such as Apache Airflow, Azure Data Factory, or Fabric pipelines
Experience with data quality and observability practices:
Validation frameworks, alerting, SLAs, monitoring
Experience optimizing performance in data environments:
