Role Overview -
We are looking for a GCP Data Engineer with 2-3 years of experience in data engineering and cloud-based development. The ideal candidate should have hands‑on experience with Python, SQL/PLSQL, Google Cloud Platform (GCP), BigQuery, Data Fusion, and Cloud Storage.
The role involves developing and maintaining scalable data pipelines and cloud-based data solutions while working with large datasets and modern GCP services.
Key Responsibilities -
- Develop and maintain data engineering solutions on GCP.
- Write, optimize, and debug SQL/PLSQL queries for data processing and analytics.
- Develop data pipelines using BigQuery, Data Fusion, and Cloud Storage.
- Use Python for data processing, automation, and integration.
- Work with Cloud Functions, Cloud Run, and/or App Engine.
- Develop data ingestion, transformation, and integration workflows.
- Process and transform structured and semi-structured data.
- Troubleshoot data pipelines and cloud-based applications.
- Monitor pipeline performance and assist with performance optimization.
- Follow best practices around scalability, security, reliability, and maintainability.
- Write unit tests and technical documentation.
- Participate in code reviews and technical discussions.
- Work with SQL and NoSQL databases as required.
- Collaborate with data engineers and cross-functional teams.
Required Skills -
- 2-3 years of experience in Data Engineering / Cloud Data Engineering.
- Hands‑on experience with Google Cloud Platform (GCP).
- Strong programming experience in Python.
- Hands‑on experience with BigQuery.
- Experience with GCP Data Fusion and data pipeline development.
- Strong knowledge of SQL and PL/SQL.
- Experience with Google Cloud Storage (GCS).
- Experience with one or more of:
- Google Cloud Functions
- Cloud Run
- App Engine
- Understanding of ETL/ELT and data integration concepts.
- Good understanding of relational and NoSQL databases.
- Experience working with large datasets.
- Strong troubleshooting and problem‑solving skills.
Good to Have -
- Knowledge of GCP IAM, security, monitoring, and logging.
- Exposure to CI/CD and DevOps practices.
- Understanding of BigQuery performance tuning and cost optimization.
- Basic knowledge of data warehouse architecture and dimensional modelling.
- Knowledge of Agile/Scrum methodologies.