● Google Cloud Platform (GCP) Tools:(Mandatory) - BigQuery, Cloud Storage, Dataflow, Cloud Functions, Pub/Sub, Cloud Run, Cloud Composer (Airflow), Cloud Spanner, Bigtable.

● Container Orchestration - Kubernetes (preferred on GKE) and Helm for managing and deploying containerized applications.

● CI/CD and Automation- Jenkins for building CI/CD pipelines to automate deployment and testing of data pipelines.

●Develop and Optimize Pipelines: Write efficient Python and SQL scripts to build data pipelines and ETL/ELT processes. Continuously monitor and optimize data workflows for performance and cost-effectiveness.

● Data Integration and Orchestration: Design workflows to integrate data from various sources using GCP services, and orchestrate complex tasks with Cloud Composer (Apache Airflow)

● Programming Languages- Proficient in Python for data processing and automation, SQL for querying and data manipulation. Experience with Java is a plus.

● DevOps Tools - Familiarity with Terraform or Deployment Manager for Infrastructure as Code (IaC) to manage GCP resources.

● Monitoring and Logging -Experience with Cloud Monitoring, Datadog, or other monitoring solutions to track pipeline performance and ensure operational efficiency.

● Data Engineering Skills Expertise in ETL/ELT pipelines, data modeling, and data integration across large datasets.

● Strong understanding of data warehousing and real-time data processing workflows.

● Strong communication skills to work effectively with cross-functional teams and mentor junior developers. Proven ability to lead in an Agile environment.

● 3+ years of experience as a data engineer, with hands-on experience in Kubernetes, Helm, Python and Jenkins.

● Strong experience building and optimizing data pipelines and services in any cloud platform.

● Proficiency in Python and SQL. Familiarity with Java and Docker is a plus.