Job Description
GCP Data Engineer

Experience:
4–10 Years Roles & Responsibilities
• Design, develop, and implement scalable data processing solutions using Big Data technologies and distributed systems
• Solid hands-on experience with Python and PySpark for developing efficient data pipelines and applications
• Develop and optimize complex SQL queries, data models, and database solutions
• Analyze and improve performance of Apache Spark workloads through optimization techniques such as partitioning, caching, tuning, and resource optimization
• Design and implement various data processing patterns including Batch Processing, Near Real-Time (NRT), and Real-Time data pipelines
• Understand business requirements and translate them into scalable data architecture and technical solutions
• Work with cloud-based data platforms and services, preferably Google Cloud Platform (GCP)
• Hands-on experience with GCP managed services such as: Google Cloud Storage, Dataproc, Dataflow, Pub/Sub,



Cloud Functions, Cloud Composer, BigQuery, BigTable . Required Skills
• 4–8 years of experience in Data Engineering / Big Data Engineering
• Strong programming experience in Python, PySpark, SQL
• Hands-on experience with Spark, Hadoop ecosystem, and distributed computing
• Experience designing scalable data pipelines and cloud-based solution
• Strong exposure to GCP data services and cloud architecture
• Good understanding of data modeling, ETL/ELT, and data integration pattern
• Experience with performance tuning and optimization of large-scale data processing workloads Good to Have
• GCP certification(s)
• Experience in enterprise cloud migration projects
• Knowledge of DevOps practices and CI/CD automation
• Experience working in Agile development environments

📌 Senior Data Engineer (Gurugram)
🏢 Impetus
📍 Gurugram