Gcp Data Engineer

Role & Responsibilities

• Design, develop, and maintain scalable data pipelines and data engineering solutions using Python and SQL.
• Develop and optimize complex SQL queries for data extraction, transformation, validation, and analysis.
• Use Python for data processing, automation, transformation, and pipeline development.
• Work with GCP or other cloud platforms to build and support cloud-based data solutions.
• Develop, monitor, troubleshoot, and maintain reliable ETL/ELT data pipelines.
• Perform data validation and ensure data quality, accuracy, consistency, and completeness.
• Troubleshoot data pipeline and production issues and identify appropriate technical solutions.
• Optimize data processing and query performance to improve efficiency and scalability.
• Collaborate with technical teams, stakeholders, and other developers to understand requirements and deliver effective data solutions.
• Maintain proper technical documentation for data pipelines, processes, and solutions.
• Follow best practices for data security, reliability, scalability, and maintainability.
• Take ownership of assigned tasks and provide timely updates on development and production activities.
• Nice to have: Work with Databricks/PySpark and Apache Airflow for data processing and workflow orchestration.

Preferred Candidate Profile

• 6+ years of relevant experience in Data Engineering, Data Development, or a closely related field.
• Strong hands-on experience with SQL and Python is mandatory.
• Good understanding of data engineering concepts, ETL/ELT processes, data pipelines, and data transformation.
• Experience with any major cloud platform such as GCP, AWS, or Azure; GCP experience is preferred.
• Candidates with hands-on experience in GCP services, particularly BigQuery, will be strongly preferred.
• Knowledge of Databricks, PySpark, or Apache Airflow will be an added advantage.
• Strong analytical and problem-solving skills with good attention to detail.
• Good understanding of data quality, validation, troubleshooting, and performance optimization.
• Excellent communication skills and the ability to confidently explain technical concepts and previous project experience.
• Should be comfortable working in a hybrid model with 3 days of Work From Office per week.

Candidate must be currently on bench and available for quick deployment.

Only bench resources should be considered; do not submit market/notice-period candidates.

UAN and LinkedIn profile are mandatory for the client screening process.

Candidates should be willing to work from Bangalore, Hyderabad, Chennai, Gurgaon, or Pune.