Fa Etqo Saasfaprod1.fa.ocs

Fa Etqo Saasfaprod1.fa.ocs

Big Data Lead

United States

Sponsorship not specifiedDetected 17 days ago
PythonData Engineering

About the role

  • Responsibilities: • Development and Maintain Data Pipelines: Design, implement, and optimize end-to-end ETL/ELT pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. • Utilize Python and Pyspark: Write efficient, scalable and maintainable code in Python and leverage Pyspark for large-scale data processing
  • in distributed computing environments. Also be able to review existing code and identify areas of improvement. • Ensure Data Quality and Integrity: Implement data validation, cleansing, transformation and reconciliation processes to ensure data accuracy and consistency throughout the data lifecycle. • Collaborate with Stakeholders: Work closely with IT

Responsibilities

  • Development and Maintain Data Pipelines: Design, implement, and optimize end-to-end ETL/ELT pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
  • Ensure Data Quality and Integrity: Implement data validation, cleansing, transformation and reconciliation processes to ensure data accuracy and consistency throughout the data lifecycle.
  • Collaborate with Stakeholders: Work closely with IT teams and business stakeholders to gather data requirements and translate them to technical solutions.
  • Troubleshoot and Optimize: Monitor job performance, troubleshoot complex data issues and fine-tune for performance and scalability.
  • Development and Maintain Data Pipelines: Design, implement, and optimize end-to-end ETL/ELT pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. • Utilize Python and Pyspark: Write efficient, scalable and maintainable code in Python and leverage Pyspark for large-scale data processing in distributed computing environments.
  • Design, implement, and optimize end-to-end ETL/ELT pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
  • Implement data validation, cleansing, transformation and reconciliation processes to ensure data accuracy and consistency throughout the data lifecycle.

This listing is sourced directly from Fa Etqo Saasfaprod1.fa.ocs's careers page and normalized into a canonical job model.