Data Engineer

We are looking for a highly skilled GCP Data Engineer with strong experience in building scalable data pipelines and working on Google Cloud Platform services. The ideal candidate will have hands-on expertise in Dataproc, Dataflow, BigQuery, and Cloud Functions and strong SQL skills to handle large-scale data processing and transformation.
Responsibilities:
Design, develop, and maintain end-to-end data pipelines on GCP.
Build and manage batch and streaming data pipelines using Dataflow (Apache Beam).
Develop and optimize Dataproc-based Spark/Hadoop workflows.
Perform data transformation, cleansing, and aggregation using SQL and BigQuery.
Create and manage serverless workflows using Cloud Functions.
Work with Cloud Composer (Airflow) for pipeline orchestration.
Handle data ingestion from multiple sources (APIs, databases, files, streams).
Ensure data quality, validation, and reconciliation across systems.
Optimize performance of pipelines and queries for large-scale datasets.
Collaborate with cross-functional teams (Data Scientists, Analysts, Business teams).
Requirements:
Strong experience in GCP Data Engineering.
Hands-on with Google Cloud Dataproc, Google Cloud Dataflow (Apache Beam), BigQuery, and Cloud Functions.
Strong proficiency in SQL (complex queries, performance tuning).
Experience working with large datasets and distributed data processing systems.
Good understanding of ETL/ELT pipelines.
Experience with batch and streaming data processing.
Preferred Skills:
Experience with Cloud Composer (Airflow).
Knowledge of Pub/Sub for streaming ingestion.
Exposure to data lake / data warehouse architecture.
Experience with Python / PySpark.
Understanding of CI/CD pipelines and DevOps practices.
Data governance, security, and compliance knowledge.

Experience
6-8 yrs