- Early StageStartup in initial stages
GCP Data Engineer
- ₹15L – ₹35L • No equity
- |+5
- |5 years of exp
- |Full Time
In office
Not Available
About the job
GCP Data Engineer – 5+ Years
Location: Bangalore / Pune / Hyderabad / Bhubaneswar / Chennai / Coimbatore
Experience: 5+ Years
Work Mode: Hybrid
Notice Period: Immediate Joiners to 30 Days preferred
About the Role
We are looking for experienced GCP Data Engineers to build and maintain scalable data pipelines, data processing solutions and cloud data platforms.
The ideal candidate should have strong hands-on experience with Python, SQL, BigQuery and Spark/PySpark/Apache Beam.
Key Responsibilities
- Design and develop scalable data pipelines on Google Cloud Platform.
- Build data ingestion and ETL/ELT solutions using Python and SQL.
- Work with large datasets and develop pipelines from source systems to data warehouses, databases and data lakes.
- Design and optimize solutions using Google BigQuery.
- Develop data processing solutions using Apache Spark, PySpark or Apache Beam.
- Work with GCP services such as Dataflow, Dataproc, Cloud SQL, GCS and Pub/Sub.
- Develop and maintain data integration and ETL processes.
- Troubleshoot data pipeline and production issues.
- Work with technical teams and business stakeholders to understand requirements.
- Ensure scalability, performance, reliability and data quality.
Must-Have Skills
- 5+ years of experience in Data Engineering.
- Strong hands-on experience with Python and SQL.
- Experience with Apache Spark / PySpark / Apache Beam.
- Strong experience with Google BigQuery.
Experience with at least one of:
- MySQL
- PostgreSQL
- SQL Server
Good to Have
- Dataflow / Dataproc.
- Cloud SQL.
- Cloud Composer / Workflows.
- Google Cloud Storage (GCS).
- Pub/Sub.
- Data Catalog.
- Experience with cloud data lakes and data warehousing.
- CI/CD and DevOps experience.
Education
B.E / B.Tech or equivalent qualification.
What We're Looking For
Strong technical and analytical skills, good communication and the ability to work with cross-functional teams in a client-facing environment.
Hybrid working model with occasional travel to client locations.
About the company
- Early StageStartup in initial stages
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