Data Engineer (GCP experienced)

Requirements:

1. 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.
2. Practical experience implementing and operating Dataplex for data governance, metadata management, and data quality across large-scale data ecosystems.
3. Strong proficiency in Oracle SQL and PL/SQL, including complex query optimization, stored procedures, performance tuning, and working with large enterprise datasets.
4. Programming experience in Python (Java/Scala as applicable) for data processing, ETL development, and pipeline automation.
5. Solid understanding of data modeling and data warehouse design principles, including dimensional modeling (star/snowflake schemas) and analytics-optimized structures.
6. Hands-on experience with Terraform and Infrastructure as Code (IaC) for provisioning and managing cloud resources in a reproducible and version-controlled way.
7. Experience building and maintaining CI/CD pipelines, supporting automated testing, deployment, and release processes for data and platform components.
8. Familiarity with Kubernetes (K8s) for deploying, scaling, and managing containerized applications in cloud environments.
9. Comfortable working in Agile/Scrum teams, participating in sprint planning, code reviews, and iterative delivery cycles.

Nice to Have:

1. Experience with Apache Spark / Databricks for large-scale data processing.
2. Knowledge of streaming architectures (Kafka, Kinesis, or Pub/Sub in advanced use cases).
3. Experience with dbt (data build tool) for transformation layer development.
4. Exposure to multi-cloud environments (GCP + AWS) and hybrid data platforms.
5. Knowledge of cost optimization in cloud data platforms (BigQuery partitioning, clustering, query optimization, FinOps basics).
6. Experience with Airflow / workflow orchestration tools (Apache Airflow, Cloud Composer).
7. Familiarity with BI tools integration (Looker, Tableau, Power BI).
8. Exposure to ML data pipelines / feature engineering pipelines (nice bonus if relevant to the company).
9. 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] Requirements: SQL, GCP, BigQuery, Dataplex, Python , CI/CD, Spark, Airflow , ML