Staff Engineer, Big Data

Nagarro; Gurugram District; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Nagarro is seeking a Senior Data Engineer in India to design and implement scalable data and cloud solutions across BigQuery, PySpark, and Python. You will optimize queries, build data pipelines, and develop serverless APIs within a Kubernetes-based environment.

The role requires 5.5+ years of experience in data/cloud engineering, with strong hands-on skills in GCP, BigQuery, SQL, and orchestration tools like Airflow. On-site opportunity based in Gurugram.

Qualifications

• 5.5+ years of overall experience in data/cloud/big data engineering.
• Hands-on experience with BigQuery and SQL, optimizing complex queries for large-scale data processing.
• Strong Python programming for scalable apps and APIs.
• Proficiency in PySpark/Spark and Hive familiarity.
• Experience with Airflow or similar orchestration services for data workflows.

Responsibilities

• Design, implement, and maintain scalable Big Data and cloud solutions using GCP, BigQuery, PySpark, and Airflow.
• Develop and maintain data workflows and pipelines with Apache Airflow and other orchestrators.
• Optimize BigQuery and SQL queries for high-volume analytics workloads.
• Develop cloud-native serverless apps using GCP Cloud Functions and Cloud Run.
• Build scalable APIs with FastAPI, Flask, or Django and containerize with Docker.
• Deploy and manage workloads on Kubernetes and implement CI/CD pipelines (GitLab CI/CD, Octopus Deploy).
• Apply Terraform IaC to provision GCP resources and configure IAM, VPC, and security.
• Collaborate with Data Engineering, Cloud, DevOps, Security, and App Teams to ensure robust solutions.
• Improve data pipelines, cloud architecture, automation, and security per industry best practices.

Skills

Big Data

Data Engineering

Cloud Engineering

Python

SQL

PySpark

Kubernetes

Airflow

Docker

GitLab CI/CD

Terraform

APIs (FastAPI/Flask/Django)

Education

Bachelor’s or Master’s degree in CS/IT or related field

Tools

BigQuery

Airflow

Docker

Kubernetes

GitLab CI/CD

Octopus Deploy

Terraform

GCP Cloud Functions

GCP Cloud Run

FastAPI

Flask

Django

Job description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (18500+ experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in!

Job Description

REQUIREMENTS:

• Total experience: 5.5+ years.
• Strong experience in Data Engineering, Cloud Engineering, or Big Data Engineering.
• Must-have expertise in Google BigQuery, Python, SQL, PySpark, GCP fundamentals, and Kubernetes.
• Strong hands‑on experience with BigQuery and SQL, including writing and optimizing complex queries for large-scale data processing.
• Strong programming experience in Python, with hands‑on experience in developing scalable applications and APIs.
• Strong experience with PySpark/Spark and familiarity with Big Data technologies such as Hive.
• Hands‑on experience with Apache Airflow or similar orchestration services for building and managing data workflows.
• Experience with GCP serverless services, particularly Cloud Functions and Cloud Run.
• Good experience with Docker and Kubernetes for containerization, deployment, orchestration, scaling, and troubleshooting.
• Experience with Python API frameworks such as FastAPI, Flask, or Django; FastAPI is preferred.
• Experience with CI/CD pipelines, preferably using GitLab CI/CD and Octopus Deploy, along with Git-based version control.
• Good understanding of Terraform and Infrastructure as Code (IaC) for provisioning and managing cloud resources.
• Good understanding of GCP networking, VPC, load balancing, IAM, API security, monitoring, logging, and alerting.
• Strong troubleshooting, analytical, problem‑solving, communication, and collaboration skills.

RESPONSIBILITIES:

• Design, implement, and maintain scalable and reliable Big Data and cloud solutions using GCP, BigQuery, PySpark, Python, and Airflow.
• Develop and maintain data workflows and pipelines using Apache Airflow and other orchestration services.
• Design, develop, and optimize BigQuery and SQL queries for high-volume data processing and analytics workloads.
• Develop and deploy cloud-native and serverless applications using GCP Cloud Functions and Cloud Run.
• Develop scalable APIs using Python frameworks such as FastAPI, Flask, or Django.
• Containerize applications using Docker and deploy, manage, and troubleshoot workloads on Kubernetes.
• Implement and maintain CI/CD pipelines for automated build, testing, and deployment using GitLab CI/CD, Octopus Deploy, or similar tools.
• Implement Infrastructure as Code (IaC) using Terraform to provision and manage GCP cloud resources.
• Configure and manage IAM policies, VPC networking, load balancing, API access controls, and security mechanisms.
• Implement monitoring, logging, alerting, and observability solutions to proactively identify and resolve system issues.
• Write comprehensive unit tests and implement quality practices to ensure application reliability and maintainability.
• Troubleshoot production issues, perform root cause analysis, and implement preventive measures to improve system stability.
• Collaborate with Data Engineering, Cloud, DevOps, Infrastructure, Security, and Application teams to deliver scalable and reliable solutions.
• Continuously improve data pipelines, cloud architecture, automation, application performance, security, and operational efficiency through industry best practices.

Qualifications

Bachelor’s or master’s degree in computer science, Information Technology, or a related field

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