About Position:

We are seeking a skilled GCP Data Engineer with 3 to 5 years of experience in designing, developing, and maintaining scalable data solutions on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in cloud-native data engineering, ETL/ELT pipeline development, Python programming, and data warehousing technologies. You will play a key role in building reliable and effective data platforms that support analytics, reporting, and business intelligence initiatives. Working closely with data analysts, data scientists, and cross-functional teams, you will help deliver scalable, high-quality, and secure data solutions.

Role: Data Engineer Location: All Persistent Locations Experience: 3 to 5 Years Job Type: Full Time Employment

What You'll Do:

Design, develop, and maintain scalable ETL/ELT data pipelines on Google Cloud Platform (GCP). Implement batch and streaming data ingestion frameworks using GCP services such as Dataflow, Dataproc, Pub/Sub, and Composer. Build, manage,



and optimize cloud-based data warehouses and data lakes using BigQuery and Cloud Storage. Develop efficient Python-based data processing, transformation, and automation solutions. Optimize data pipelines for performance, scalability, reliability, and cost efficiency. Extract, transform, and load data from multiple sources including APIs, databases, flat files, and streaming platforms. Work with structured, semi-structured, and unstructured datasets to support business requirements. Ensure data quality, integrity, governance, and compliance across all data pipelines and platforms. Collaborate with data analysts, data scientists, architects, and business stakeholders to deliver data-driven solutions. Troubleshoot and resolve data pipeline performance issues and production incidents. Document data workflows, schemas, architectures, and processes to ensure maintainability and knowledge sharing. Participate in code reviews and contribute to engineering best practices

📌 Data Engineer (Pune)
🏢 Persistent Systems
📍 Pune