Description

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 and standards.

Expertise You'll Bring:

• 3 to 5 years of hands-on experience in Data Engineering and cloud-based data platform development.
• Strong experience with Google Cloud Platform (GCP) services including BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Composer.
• Strong programming expertise in Python for data engineering, automation, and transformation workloads.
• Good understanding of SQL development, query optimization, and performance tuning techniques.
• Hands-on experience designing and implementing ETL/ELT pipelines.
• Experience with batch and real-time streaming data processing.
• Strong understanding of data modeling, schema design, and data warehousing concepts.
• Familiarity with data formats such as Parquet, Avro, JSON, and CSV.
• Experience integrating data from APIs, databases, and external systems.
• Knowledge of cloud-native architecture patterns and modern data engineering practices.
• Understanding of data quality frameworks, monitoring, and governance principles.
• Strong analytical, troubleshooting, and problem-solving skills.
• Experience working in Agile development environments.
• Excellent communication and collaboration skills with cross-functional teams.

Key Skills

Education

Any Graduate