Gcp Data Engineer

IntraEdge Technology; Gurugram District; Hybrid; INR 1,500,000 - 2,200,000; Full time

Job summary

IntraEdge Technology is seeking an experienced Data Engineer with strong Google Cloud Platform expertise to design, build, and scale modern cloud-native data solutions and platforms.

You will design scalable data architectures, develop reliable data pipelines, and contribute to engineering practices that improve performance, resiliency, and operational excellence.

Qualifications

• 5+ years of data engineering or related software engineering experience.
• Strong hands-on experience with Google Cloud Platform (GCP) and building production-grade cloud data solutions.
• Strong experience with BigQuery and at least one messaging or distributed processing tech such as Pub/Sub, Kafka, Spark, or PySpark.
• Strong programming experience with Python.
• Experience designing and developing data pipelines and high-volume data workloads.
• Experience with Apache Airflow or similar workflow orchestration.
• Understanding of cloud architecture, data integration patterns, scalability, and resiliency.
• Experience with CI/CD and DevOps tooling.

Responsibilities

• Design, develop, test, and deploy scalable cloud-native data solutions on GCP.
• Build data processing and integration solutions using GCP services (BigQuery, Pub/Sub, Dataproc, etc).
• Contribute to data architecture, system design, and performance improvements.
• Develop software and data engineering solutions using Python following best practices.
• Design batch, streaming, and event-driven data processing with Pub/Sub, Kafka, Spark, and REST APIs.
• Develop and orchestrate data workflows with Apache Airflow.
• Build reliable data pipelines for high-volume distributed workloads.
• Support CI/CD, monitoring, observability, and production support.

Skills

Python

Distributed systems

Data engineering

Cross-functional collaboration

Education

Bachelor's or Master's in Computer Science, Engineering, Information Systems

Tools

BigQuery

Pub/Sub

Cloud Spanner

Dataproc

Bigtable

Apache Airflow

Kafka

Spark/PySpark

Job description

We are looking for an experienced Data Engineer with strong Google Cloud Platform (GCP) expertise to design, build, and scale modern cloud-native data solutions and platforms.

The ideal candidate has experience building production-grade data solutions on GCP, along with strong programming, data engineering, and distributed systems fundamentals. The role will involve designing scalable data architectures, developing reliable data pipelines and applications, and contributing to engineering practices that improve performance, resiliency, and operational excellence.

Responsibilities

• Design, develop, test, and deploy scalable, resilient, and maintainable cloud-native data solutions and platforms on GCP.
• Build data processing and integration solutions leveraging GCP services such as BigQuery, Pub/Sub, Cloud Spanner, Dataproc, and Bigtable.
• Contribute to solution and data architecture, including system design, integration patterns, scalability, resiliency, security, and performance.
• Develop high-quality software and data engineering solutions using Python, following sound software engineering practices.
• Design and implement batch, streaming, and event-driven data processing solutions using technologies such as Pub/Sub, Kafka, Spark/PySpark, and REST APIs.
• Develop, schedule, and orchestrate data workflows using Apache Airflow and DAGs.
• Build and maintain reliable data pipelines supporting high-volume and distributed workloads.
• Contribute to automated testing, CI/CD, deployment automation, monitoring, observability, and production support.
• Troubleshoot production issues and continuously improve the reliability, performance, and maintainability of data platforms.
• Collaborate with engineering, architecture, product, and other cross-functional teams to deliver scalable data solutions.

Minimum Qualifications

• 5+ years of data engineering or related software engineering experience, including experience building and supporting enterprise-scale data applications or platforms.
• Strong hands‑on experience with Google Cloud Platform (GCP) and building production-grade cloud data solutions.
• Strong experience with BigQuery and at least one messaging, streaming, or distributed data processing technology such as Pub/Sub, Kafka, Spark, or PySpark.
• Strong programming experience with Python.
• Experience designing and developing data pipelines, distributed data processing, and high‑volume data workloads.
• Experience with Apache Airflow or a comparable workflow orchestration platform.
• Understanding of cloud architecture and data integration patterns, including batch and event‑driven processing, data storage, scalability, and resiliency.
• Experience with production engineering practices, including monitoring, troubleshooting, performance optimization, automated testing, and CI/CD.
• Strong problem‑solving, communication, and cross‑functional collaboration skills.

Preferred Qualifications

• Bachelors or Master’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• Hands‑on experience with additional GCP data services such as Cloud Spanner, Dataproc, and Bigtable.
• Experience with Spark/PySpark and large‑scale distributed data processing.
• Experience with Kafka or other event‑streaming technologies.
• Experience designing distributed systems, microservices, and RESTful APIs.
• Knowledge of software design fundamentals, including object‑oriented design, SOLID principles, design patterns, data structures, algorithms, and API design.
• Experience with CI/CD and DevOps tooling such as GitHub Actions, Jenkins, or Maven.
• Experience with containerization and orchestration technologies such as Docker, Kubernetes, or OpenShift.
• Experience with data quality, governance, security, and observability practices in cloud data platforms.
• Experience using AI-assisted development tools to improve engineering productivity, code quality, testing, or documentation.