𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟭𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟭𝟬-𝟮𝟬 𝗟𝗣𝗔)

Experience: 3+ yrs

Location: Bengaluru, Karnataka, India, Chennai, Tamil Nadu, India

Job Type: Full-time

We are looking for a skilled GCP Data Engineer to design, develop, and optimize scalable cloud-based data platforms using Google Cloud Platform (GCP). This role is ideal for professionals with strong expertise in Python, PySpark, and modern data engineering practices who are passionate about building reliable, high-performance data pipelines that power analytics, reporting, and machine learning initiatives.

As a GCP Data Engineer, you will collaborate with data architects, analysts, data scientists, and application teams to build robust data solutions that process large volumes of structured and unstructured data. You will play a key role in designing cloud-native data pipelines, optimizing data processing workloads, ensuring data quality, and implementing best practices for scalability, security, and performance. This position offers the opportunity to work with modern cloud technologies while contributing to enterprise-wide data transformation initiatives.

Requirements

Key Responsibilities

• Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP) for batch and real-time data processing.
• Build robust ETL/ELT workflows using Python, PySpark, and cloud-native data processing frameworks.
• Develop and optimize data ingestion pipelines from multiple enterprise systems, APIs, databases, and streaming platforms.
• Work with BigQuery, Cloud Storage, Dataproc, Dataflow, Pub/Sub, and other GCP services to deliver efficient data solutions.
• Transform, cleanse, validate, and enrich large datasets while maintaining high standards of data quality and consistency.
• Optimize data processing performance, resource utilization, and cloud infrastructure costs across GCP environments.
• Collaborate with data architects, analytics teams, and business stakeholders to understand requirements and implement scalable data models.
• Implement monitoring, logging, error handling, and automated recovery mechanisms for production data pipelines.
• Develop reusable data engineering frameworks, automation scripts, and deployment processes following DevOps best practices.
• Create and maintain technical documentation, data lineage, and operational procedures while supporting continuous improvement initiatives.

What Makes You a Great Fit

• 3+ years of hands-on experience in Data Engineering with strong expertise in Google Cloud Platform (GCP).
• Strong programming skills in Python and PySpark for large-scale data transformation and processing.
• Experience working with GCP services such as BigQuery, Dataproc, Dataflow, Cloud Storage, Pub/Sub, Composer, or equivalent cloud-native technologies.
• Solid understanding of ETL/ELT development, distributed data processing, and cloud data architectures.
• Experience designing scalable data models, optimizing SQL queries, and improving pipeline performance.
• Familiarity with workflow orchestration tools, CI/CD pipelines, version control systems, and DevOps practices.
• Good understanding of data quality, governance, security, and monitoring best practices in cloud environments.
• Strong analytical, debugging, and problem-solving skills with the ability to work on complex data engineering challenges.
• Excellent communication and collaboration skills with experience working across cross-functional engineering and analytics teams.
• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related discipline, with a passion for building modern cloud-based data platforms.