Lead Data Engineer
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Job Description
Lead Data Engineer developing PySpark data solutions for U.S. clients in a 100% remote role from Latin America. Collaborate with cross-functional teams to meet business requirements.
Responsibilities:
- Work with one of our U.S.-based clients.
- Develop and implement data pipelines using PySpark.
- Collaborate with cross-functional teams including machine learning engineers, software developers, analytics engineers, and product managers.
- Translate business requirements into highly available data solutions.
- Maintain and improve existing data pipelines and systems.
Requirements:
- 8+ Years of total experience collaborating with cross-functional teams, including machine learning engineers, software developers, analytics engineers, and product managers to translate business requirements into highly available data solutions
- 3+ years of experience developing and implementing data pipelines using PySpark.
- Proven experience with SQL
- Advanced written and Spoken English (B2 or C1/C2).
- Good to have Databricks Certification
- Good to have Experience providing practical direction within azure native services , implementing data migration and data processing using Azure services: ADLS, Azure Data Factory, Synapse/DW /Azure SQL DB, Fabric.
- Good to have Event Hub, IOT Hub, Azure Stream Analytics, Azure Analysis Service, Cosmo Db knowledge.
- Good to have SAP Hana knowledge
- Intermediate knowledge on Power BI
- Good to have knowledge in DevOps and CI/CD deployments, Cloud migration methodologies and processes
Benefits:
- Contract Type: Independent contractor (no paid holidays or vacation, tax deductions, or insurance)
- Compensation is based on gross monthly payment for hours worked
- Equipment: You must use your own laptop or PC.
- Onboarding process: Onboarding begins after candidate selection and includes an in-person identity verification due to the end client’s security requirements.
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