Cloud Engineering Professional

6 days ago

Ellore, Andhra Pradesh, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Cloud Data Engineer Job Description

About this role

This Cloud Data Engineer position involves designing and developing scalable ETL pipelines using cloud-native tools.

The ideal candidate will have extensive experience with cloud-native ETL tools such as AWS DMS, AWS Glue, Kafka, Azure Data Factory, GCP Dataflow, and other ETL tools like Informatica, SAP Data Intelligence, etc.

Key Responsibilities:

  • Design and Development:
    • Design, develop, and maintain scalable ETL pipelines using cloud-native tools (AWS DMS, AWS Glue, Kafka, Azure Data Factory, GCP Dataflow, etc.).
    • Architect and implement data lakes and data warehouses on cloud platforms (AWS, Azure, GCP).
    • Develop and optimize data ingestion, transformation, and loading processes using Databricks, Snowflake, Redshift, BigQuery and Azure Synapse.
    • Implement ETL processes using tools like Informatica, SAP Data Intelligence, and others.
    • Develop and optimize data processing jobs using Spark Scala.
  • Data Integration and Management:
    • Integrate various data sources, including relational databases, APIs, unstructured data, and ERP systems into the data lake.
    • Ensure data quality and integrity through rigorous testing and validation.
    • Perform data extraction from SAP or ERP systems when necessary.
  • Performance Optimization:
    • Monitor and optimize the performance of data pipelines and ETL processes.
    • Implement best practices for data management, including data governance, security, and compliance.
  • Collaboration and Communication:
    • Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
    • Collaborate with cross-functional teams to design and implement data solutions that meet business needs.
  • Documentation and Maintenance:
    • Document technical solutions, processes, and workflows.
    • Maintain and troubleshoot existing ETL pipelines and data integrations.

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