๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ญ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฎ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ญ๐ฌ-๐ฎ๐ฌ ๐๐ฃ๐)
Experience: 3+ yrs
Location: Bengaluru, Karnataka, India, Chennai, Tamil Nadu, India
Job Type: Full-time
We are looking for a skilledย GCP Data Engineerย to design, develop, and optimize scalable cloud-based data platforms usingย Google Cloud Platform (GCP). This role is ideal for professionals with strong expertise inย Python,ย 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 onย Google Cloud Platform (GCP)ย for batch and real-time data processing.
- Build robust ETL/ELT workflows usingย Python,ย 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 inย Data Engineeringย with strong expertise inย Google Cloud Platform (GCP).
- Strong programming skills inย Pythonย andย PySparkย 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.