Gcp Data Engineer

Job Requirements*

- Proficiency in programming languages: Python, Java

- Expertise in data processing frameworks: Apache Beam (Data Flow)

- Active experience on GCP tools and technologies like Big Query, Dataflow, Cloud Composer, Cloud Spanner, GCS, DBT etc.,

- Data Engineering skillset using Python, SQL

- Experience in ETL (Extract, Transform, Load) processes

- Knowledge of DevOps tools like Jenkins, GitHub, Terraform is desirable. Should have good knowledge on Kafka (Batch/ streaming)

- Understanding of Data models and experience in performing ETL design and build, database replication using Message based CDC

- Familiarity with cloud storage solutions

- Strong problem-solving abilities in data engineering challenges

- Understanding of data security and scalability

• - Proficiency in relevant tools like Apache Airflow

Core Skills:

• GCP Services: BigQuery, Dataflow, Cloud Storage, Pub/Sub, Data Catalog, Data Fusion, AI Platform.
• Programming: SQL, Python, Java/Scala(for Dataflow/Spark).
• Data Concepts: Data Warehousing, ETL, Data Modeling, Streaming.
• Tools: Apache Beam, Docker, Kubernetes, Git,Terraform.

Key Responsibilities*

• Design & Build Data Pipelines: Develop scalable data ingestion, transformation (ETL/ELT), and orchestration workflows using GCP services.
• GCP Service Utilization: Implement solutions with BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, and Cloud Composer.
• Data Integration: Connect and manage data from diverse sources (APIs, databases, files).
• Optimization: Improve performance, cost-efficiency, and reliability of data processes.
• Collaboration: Work with data scientists, analysts, and architects to meet data needs.
• Quality & Security: Ensure data integrity, security, and compliance.
• Automation: Implement CI/CD and Infrastructure as Code (IaC) using tools like Terraform.
• Monitoring & Support: Maintain, monitor, and troubleshoot data workloads and systems.