Senior Data Engineer

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
• Strong 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

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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