Google Cloud Platform Data Engineers and Google Cloud Platform Architects--Need only Locals--F2F Mandate

Job Summary:

We are seeking a skilled Google Cloud Platform (Google Cloud Platform) Data Engineer to design, build, and optimize data pipelines and analytics solutions in the cloud. The ideal candidate must have hands-on experience with Google Cloud Platform data services, strong ETL/ELT development skills, and a solid understanding of data architecture, data modeling, data warehousing and performance optimization.

Key Responsibilities:

•        Develop ETL/ELT processes to extract data from various sources, transform it, and load it into BigQuery or other target systems.

•        Build and maintain data models, data warehouses, and data lakes for analytics and reporting.

•        Design and implement scalable, secure, and efficient data pipelines on Google Cloud Platform using tools such as Dataflow, Pub/Sub, cloud run, Python and linux scripting.

•        Optimize BigQuery queries, manage partitioning and clustering, and handle cost optimization.

•        Integrate data from on-premise and cloud systems using Cloud Storage, and APIs.

•        Work closely with DevOps teams to automate deployments using Terraform, Cloud Build, or CI/CD pipelines.

•        Ensure security and compliance by applying IAM roles, encryption, and network controls.

•        Collaborate with data analysts, data scientists, and application teams to deliver high-quality data solutions.

•        Implement best practices for data quality, monitoring, and governance.

Required Skills and Experience:

•        Bachelor’s degree in Computer Science, Information Technology, or related field.

•        Minimum 8 years of experience in data engineering, preferably in a cloud environment.

•        Minimum 3 years of hands-on and strong expertise in Google Cloud Platform services:

·         BigQuery, Cloud storage, Cloud run, Dataflow, Cloud SQL, AlloyDB, Cloud Balancer, PubSub, IAM, Logging and Monitoring.

•        Proficiency in SQL, Python and Linux scripting.

•        Prior experience with ETL tools such as Datastage, Informatica, SSIS

•        Familiarity with data modeling (star/snowflake) and data warehouse concepts.

•        Understanding of CI/CD, version control (Git), and Infrastructure as Code (Terraform).

•        Strong problem-solving and analytical mindset.

•        Effective communication and collaboration skills.

•        Ability to work in an agile and fast-paced environment.

•        Google Cloud Platform Professional Data Engineer or Cloud Architect certification is a plus