Gcp Data Engineer

Reliable Group Paragon; United States; Remote; USD 12,000 - 22,000; Full time

Job summary

Reliable Group Paragon in Pune/Remote is seeking an experienced GCP Data Engineer to design, develop, and maintain scalable ETL/ELT pipelines on Google Cloud Platform. The role requires hands-on experience with BigQuery, Dataflow, Airflow, Python, and SQL, and working with large distributed data processing systems.

You will collaborate with analytics and engineering teams to deliver robust data solutions using modern cloud-native architectures and CI/CD practices.

Qualifications

• Ideal candidate has 4+ years in data engineering or ETL development.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines on GCP.
• Build and optimize pipelines using BigQuery, Dataflow, and Airflow/Cloud Composer.
• Develop data processing solutions using Python and SQL.
• Work with large datasets and distributed data processing environments.
• Design reliable, scalable, fault-tolerant data processing systems.
• Integrate data from multiple sources into cloud-based data platforms.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Implement data quality, validation, monitoring, and error-handling mechanisms.
• Collaborate with engineering, analytics, and other teams to deliver data solutions.

Skills

ETL/ELT

GCP

BigQuery

Dataflow

Airflow

Python

SQL

Kubernetes

CI/CD

Vertex AI

Distributed systems

Data warehousing

Job description

Job Title: GCP Data Engineer
Experience: 4-8 Years
Location: Pune / Remote
Employment Type: Full-time

Job Summary:

We are looking for an experienced GCP Data Engineer with strong hands-on expertise in Google Cloud Platform (GCP) and modern data engineering technologies. The ideal candidate will have experience designing, developing, and supporting scalable data pipelines and distributed data processing systems.

Key Responsibilities:

• Design, develop, and maintain scalable ETL/ELT data pipelines on GCP.
• Build and optimize data pipelines using Google BigQuery, Dataflow, and Cloud Composer/Airflow.
• Develop efficient data processing solutions using Python and SQL.
• Work with large datasets and distributed data processing environments.
• Design reliable, scalable, and fault-tolerant data processing systems.
• Integrate data from multiple sources into cloud-based data platforms.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Implement data quality, validation, monitoring, and error-handling mechanisms.
• Collaborate with engineering, analytics, and other technical teams to deliver data solutions.
• Follow best practices around coding, testing, CI/CD, security, and cloud architecture.

Required Skills:

• 4+ years of experience in Data Engineering / ETL development.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Strong experience with BigQuery.
• Hands-on experience with Dataflow / Apache Beam.
• Experience with Cloud Composer / Apache Airflow.
• Strong programming experience in Python.
• Strong SQL skills.
• Experience working with distributed systems and large-scale data processing.
• Understanding of data warehousing, ETL/ELT, and data pipeline architecture.
• Experience with microservices / scalable system architecture is an advantage.
• Experience with Kubernetes / GKE is preferred.
• Experience with CI/CD and cloud-based development practices.
• Vertex AI or exposure to AI/ML platforms is a plus.

Preferred Qualifications:

• Experience designing highly scalable and fault-tolerant data platforms.
• Experience with GKE/Kubernetes.
• Experience with data-centric system design.
• Experience with cloud-native architectures.
• Exposure to Vertex AI or machine learning workloads.