Jobs / Wip***
Data Engineer
Wip*** · Mount Laurel, NJ, United States
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Mount Laurel, NJ, United States60,000-135,000 USD/yearlyHybrid
Remuneration
60,000-135,000 USD/yearly
Location
Mount Laurel, NJ, United States
Visa sponsorship
Sponsors visa
Job summary
Job Title: Data Engineer City: MOUNT LAUREL State/Province: New Jersey Posting Start Date: 7/27/26 Wip*** Limited (NYSE: WIT, BSE: 507685, NSE: Wip***) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs.
Benefits
Including a full range of medical and dentalOptions, disability insurance, paid time off (inclusive of sick leave), other paApplications from veterans and people with disabilities are explicitly welcome.Reinvent your world.We are building a modern Wipro.We are an end-to-end digital transformation partner with the boldest ambitions.To realize them, we need people inspired by reinvention.Of yourself, your career, and your
Qualifications
- We are looking for a skilled Data Engineer with strong hands-on experience in Azure Databricks and Azure Data Factory to design, develop, and maintain scalable data pipelines and cloud-based data solutions.
- and deliver data solutions.
- Implement data validation, reconciliation, exception handling, logging, and alerting mechanisms.
- Follow coding standards, version control, CI/CD, and deployment best practices using
Responsibilities
- Design, develop, and maintain scalable data pipelines using Azure Data Factory and Azure Databricks.
- Build ETL/ELT workflows for data ingestion, transformation, cleansing, enrichment, and loading into data lakes or data warehouses.
- Develop and optimize PySpark, Spark SQL, and SQL scripts for large-scale data processing.
- Integrate data from multiple sources such as databases, APIs, flat files, cloud storage, and enterprise applications.
- Implement incremental data loading, scheduling, parameterization, and reusable pipeline frameworks in ADF.
- Work with Azure Data Lake Storage, Delta Lake, and lakehouse architecture patterns for structured and unstructured data.
- Monitor, troubleshoot, and optimize data pipelines for performance, reliability, cost efficiency, and data quality.
- Collaborate with business users, data analysts, data scientists, and architects to understand
Degrees
Associate
Industry
EnergyInsuranceLogisticsManufacturingMediaPublic-sector
Company size
Enterprise
Contract length
8 years