AWS / Azure Data Engineer

Design, implement, and manage scalable ETL / ELT pipelines using AWS services and Databricks.

• Data Integration :

Ingest and process structured, semi-structured, and unstructured data from multiple sources into AWS Data Lake or Databricks.

• Data Transformation :

Develop advanced data processing workflows using PySpark, Databricks SQL, or Scala to enable analytics and reporting.

• Databricks Management :

Configure and optimize Databricks clusters, notebooks, and jobs for performance and cost efficiency.

• AWS Architecture :

Design and implement solutions leveraging AWS-native services like S3, Glue, Redshift, EMR, Lambda, Kinesis, and Athena.

• Collaboration :

Work closely with Data Analysts, Data Scientists, and other Engineers to understand business requirements and deliver data-driven solutions.

• Performance Tuning :

Optimize data pipelines, storage, and queries for performance, scalability, and reliability.

• Monitoring and Security :

Ensure data pipelines are secure, robust, and monitored using CloudWatch, Datadog, or equivalent tools.

• Documentation :

Maintain clear and concise documentation for data pipelines, workflows, and architecture