GCP Data Engineer

Note:

(GC, GC-EAD, OPT, CPT on C2C will not be workable)

• Design, implement, and optimize clean, well-structured, and performant analytical datasets to support high-volume reporting, business analysis, and data science model development.
• Architect, build, and maintain scalable and robust data pipelines for diverse applications, including business intelligence and advanced analytics.
• Implement and support Big Data solutions for both batch (scheduled) and real-time/streaming analytics.
• Work closely with product managers and business teams to understand data requirements and translate them into technical solutions.
• Collaborate with Dev Ops teams to ensure smooth deployment, monitoring, and maintenance of data pipelines and infrastructure in cloud environments.

• Cloud Platform Expertise (GCP Focus):
  Extensive hands-on experience working in dynamic cloud environments, with a strong preference for Google Cloud Platform (GCP) services, specifically:
• Big Query:
  Expert-level skills in data ingestion, performance optimization, and data modeling within a petabyte-scale environment.
• Experience with other relevant GCP services like Cloud Storage, Cloud Dataflow/Beam, or Pub/Sub.
• Python:
  Expert-level programming proficiency in Python, including experience with relevant data engineering libraries.
• SQL: A solid command of advanced SQL for complex querying, data processing, and performance tuning.

• Data Pipeline Orchestration:
  Prior experience using workflow management and orchestration tools (e.g., Apache Airflow, Cloud Composer, Dagster, or similar).

• Dev Ops/CI/CD:
• Strong understanding of Dev Ops principles and practices.
• Experience with CI/CD pipelines, automation tools, and deployment strategies.
• Familiarity with version control systems (Git) and tools like Git Lab CI/CD, Git Hub Actions, or Jenkins.
• Knowledge of containerization (Docker) and orchestration tools (Kubernetes) is a plus.

• Monitoring & Automation:
  Ability to implement monitoring solutions and automate operational tasks to ensure reliability and scalability.