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World Business Lenders, LLC is seeking a Data Engineer contractor to design and optimize data pipelines, migrate legacy systems, and ensure data quality across the organization. The role emphasizes automation, reliability, and collaboration with analytics and business teams.
Candidates should have 4–7 years of data engineering experience, strong SQL and Python skills, and experience with cloud data platforms and ETL/ELT processes.
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.
4 to 7 years of experience as a Data Engineer.
We value practical, hands‑on expertise that goes beyond just theoretical knowledge.
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).
Must be available to work Monday–Friday, 9:00 AM – 6:00 PM Eastern Time.
Must have a stable internet connection and professional remote working setup.
Resume must be submitted in English to be considered.
Compensationin USD.
Benefitsinclude paid time off (PTO).
Work Environment:Fully remote work environment.