Description
You will design and implement data pipelines across cloud environments to handle structured, semi-structured, and unstructured data.
Responsibilities
- Build and maintain data pipelines using cloud-native integration services.
- Manage data storage and warehousing across cloud data lakes and database solutions.
- Implement cloud compute services and load balancing to support data workloads.
- Configure cloud identity management, authentication, and authorization protocols.
- Develop and deploy serverless utility functions for data processing tasks.
Required Skills
- 9+ years of experience in data engineering roles.
- Hands-on experience with at least one Generative AI project.
- Proven experience implementing data pipelines in AWS, Azure, or GCP.
- Proficiency with cloud storage and data warehousing such as Snowflake, BigQuery, AWS Redshift, ADLS, or S3.
- Experience with Azure Databricks, Azure Data Factory, Azure Synapse Analytics, AWS Glue, AWS EMR, Dataflow, or Dataproc.
- Practical use of cloud functions including AWS Lambda, AWS Step Functions, Cloud Run, Cloud Functions, or Azure Functions.
- Working knowledge of cloud compute services and load balancing.
- Understanding of cloud identity management, authentication, and authorization.