Data Engineering Analyst

Description

Summary: World Business Lenders is seeking Data Analysts specializing in data engineering & migration or data pipeline & automation to improve data processes and system performance. Highlights: 1. Opportunity to enhance data accuracy, consistency, and reliability. 2. Chance to migrate legacy systems to new, improved platforms. 3. Work on building and maintaining automated data pipelines. **About World Business Lenders** Learn more about us: **\[Who We Are]** World Business Lenders (WBL) is proud to offer short\-term, real estate\-backed commercial loans to a diverse range of small and medium\-sized businesses across the United States, especially those who may find it challenging to secure traditional financing. Typically, the work schedule is from 9:00am to 6:00pm Eastern Time, Monday through Friday, though there might be times when additional hours are needed to meet business demands. **We’re looking for someone with strong communication skills in both English, both spoken and written.** * ***Please note that all resumes should be submitted in English.*** **We are seeking two Data Analysts, one specializing in data engineering \& migration, and another focused on data pipeline \& automation. Candidates with strengths in either area are encouraged to apply.** **Key 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** **Required Education:** * 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! **Required 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:** **Required for both roles:** * 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, including:** * Schema mapping, transformation, and migration of legacy systems to new platforms * Preserving business keys and maintaining data integrity throughout migration activities * Data reconciliation and validation between source and target systems * Identifying data inconsistencies, lineage gaps, and potential migration risks * Performing data quality checks, integrity validation, and issue resolution * Creating exception reports, control outputs, and auditable migration documentation * Managing backfills and historical data handling * Supporting cutover planning, execution, and post\-migration validation **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: * 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 **Key Soft Skills:** * 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). **Technical Skills:** * Proficiency in SQL, Python, cloud technologies, and data competency. **Benefits** **What We Offer** USD compensation ️ Paid Time Off (PTO) Fully remote — work from wherever you do your best work! **Ready to Apply?** *If this sounds like you, we'd love to hear from you \- submit your CV in English and hit* ***Apply!***