Data Engineer (GCP experienced)

• Strong hands-on experience with Google Cloud Platform (GCP), including BigQuery, Dataplex, Dataflow, and Pub/Sub for building and supporting scalable data pipelines in production environments
• Practical experience implementing and operating Dataplex for data governance, metadata management, and data quality across large-scale data ecosystems
• Strong proficiency in Oracle SQL and PL/SQL, including complex query optimization, stored procedures, performance tuning, and working with large enterprise datasets
• Programming experience in Python (Java/Scala as applicable) for data processing, ETL development, and pipeline automation
• Solid understanding of data modeling and data warehouse design principles, including dimensional modeling (star/snowflake schemas) and analytics-optimized structures
• Hands-on experience with Terraform and Infrastructure as Code (IaC) for provisioning and managing cloud resources in a reproducible and version-controlled way
• Experience building and maintaining CI/CD pipelines, supporting automated testing, deployment, and release processes for data and platform components
• Familiarity with Kubernetes (K8s) for deploying, scaling, and managing containerized applications in cloud environments
• Comfortable working in Agile/Scrum teams, participating in sprint planning, code reviews, and iterative delivery cycles

Nice to have:

• Experience with Apache Spark / Databricks for large-scale data processing
• Knowledge of streaming architectures (Kafka, Kinesis, or Pub/Sub in advanced use cases)
• Experience with dbt (data build tool) for transformation layer development
• Exposure to multi-cloud environments (GCP + AWS) and hybrid data platforms
• Knowledge of cost optimization in cloud data platforms (BigQuery partitioning, clustering, query optimization, FinOps basics)
• Experience with Airflow / workflow orchestration tools (Apache Airflow, Cloud Composer)
• Familiarity with BI tools integration (Looker, Tableau, Power BI)
• Exposure to ML data pipelines / feature engineering pipelines
• Experience with event-driven architectures and microservices integration patterns

• Designing scalable, secure pipelines across GCP (BigQuery, Dataflow, Pub/Sub) and AWS
• Implementing governance and data domain structures using Dataplex
• Integrating cloud platforms with Oracle databases
• Delivering both real-time and batch data solutions
• Optimizing systems for performance and latency
• Automating infrastructure with Terraform
• Building CI/CD workflows
• Working with Docker & Kubernetes
• Collaborating in Agile/Scrum teams
• Ensuring governance, lineage, and compliance standards