Data Engineering Analyst

🕒 April 7

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World Business Lenders, LLC

WebsiteLinkedInAll Job Openings

201 - 500 employees

💸 Finance

🤝 B2B

💳 Fintech

Finance • B2B • Fintech

World Business Lenders, LLC is a direct lender that specializes in providing real-estate secured business loans to small-to-medium-sized businesses. The company focuses on serving under-served businesses that lack access to traditional funding, facilitating access to capital for business expansion and growth. With a strong management team experienced in financial services, World Business Lenders offers working capital solutions to foster the development of successful small businesses.

📋 Description

• 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

• A Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field is preferred — but we also highly value equivalent hands-on experience! • 4 to 7 years of experience as a Data Engineer. • 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 • 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 • Experience building and maintaining automated data pipelines: • Scheduling, orchestration, and failure handling • Workflow reliability, monitoring, and repeatability • 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: • Query tuning, partitioning, indexing, cost optimization • Familiarity with modern data formats and large-scale processing: • Parquet, Delta, incremental processing patterns • Experience integrating with external systems: • REST APIs, authentication, retries, error handling • Exposure to CI/CD practices for data workflows: • Git-based deployments, PR workflows, environment promotion • Clear communication: can explain data issues, tradeoffs, and results to both technical and business stakeholders. • Ownership & accountability: takes end-to-end responsibility for pipelines, data quality, and outcomes. • Problem-solving mindset: able to debug complex data issues and work through ambiguity independently. • Collaboration: works effectively across engineering, analytics, and business teams. • Adaptability: comfortable operating in evolving environments (migration, changing requirements, new tools).

🏖️ Benefits

• USD Base Salary. • Enjoy Paid Time Off (PTO) after just 6 months of service. • Full-time opportunity. • Enjoy the freedom of a completely remote work environment!