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- In-depth understanding of Google's product technology and underlying architectures
- BigQuery – Warehouse/ data marts – Through understanding of Big Query internals to write efficient queries for ELT needs, creation of views/materialized views, creation of reusable store procedures etc.
- DataFlow (Apache Beam) – reusable Flex templates/ data processing frameworks using Java for both batch and stream needs.
- Pub/Sub, Kafka, Confluent Kafka – Real time streaming of database changes or events.
- Experience of designing, building, and deploying production-level data pipelines using Kafka; Strong experience working on Event Driven Architecture
- Strong knowledge of the Kafka Connect framework, with experience using several connector types HTTP REST proxy, JMS, File, SFTP, JDBC etc.
- Experience in handling huge volumes of streaming messages from Kafka
- Cloud Composer (Apache Airflow) – to build, monitor and orchestrating the pipeline
- Knowledge on BigTable
- Cloud SQL, Compute Engine, Cloud Function, Cloud Run and App Engine, Cloud Storage
- Experience with open-source distributed storage and processing utilities in the Apache Hadoop family.
- Extensive knowledge on processing various file formats orc, Avro, csv, json, xml etc.
- Knowledge/experience in any ETL tools like DataStage/Informatica – Ability to understand existing on-premises ETL workflows and redesign them in Google Cloud Platform.
- Experience and expertise on Terraform to deploy the Google Cloud Platform’s in CI/CD.
- Knowledge/ Experience on connecting to on-prem API’s from google cloud.