Walk-in || Data Engineer

Role & responsibilities

GCP data engineers create and maintain data systems on Google Cloud Platform. Their roles and responsibilities focus on using tools like BigQuery, Dataflow, and Pub/Sub to build pipelines, manage cloud storage, and enable real-time data processing for fast, reliable analytics.

Preferred candidate profile

• Technical skills:
• Experience with GCP data engineering components like cloud run functions, cloud scheduler, workflow, pub/sub, GCS, dataflow, Bigquery, cloud build.
• Deployment using GitHub actions, Jenkins
• Deep query language experience (SQL / PL-SQL), Python, and object-oriented languages (Java, Python); developing APIs.
• Data Warehousing & Modelling:
• Top-down & bottom-up database design, data masking, normalization, denormalization, and dimensional modeling.
• Designing scalable fact/dimension schemas in cloud data warehouses.
• Big Data & Streaming:
• Handling structured, semi-structured, and unstructured data at scale.
• Experience with streaming architectures, NoSQL stores, and key-value databases under high concurrency and volume.
• ETL / ELT Pipelines:
• Building data pipelines with rollback strategies, bad-record handling, and performance optimization.
• Designing end-to-end data integration flows.

Ensuring Data Quality and Governance

Another critical role and responsibility of a data engineer is to implement checks and policies to ensure data quality, security, and compliance. This involves validating data accuracy and protecting sensitive information.