GCP Data Engineer

Jobtailor

Gurugram District

On-site

INR 1,800,000 - 3,200,000

Full time

2 days ago

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Job summary

Jobtailor in Gurugram, Haryana, India seeks a senior data engineer to design and implement scalable data pipelines on GCP, focusing on BigQuery, Dataproc, Dataflow, and Pub/Sub.

The role involves collaborating with data analysts and business stakeholders, building data warehouses, and ensuring reliable ETL/ELT processes using Python/Scala, Airflow, and CI/CD.

Qualifications

Graduate in Computer Science, or related field.
6+ years of experience in data engineering or related field.
Proficiency in GCP big data tools, including BigQuery, Dataproc, Airflow, Dataflow, and Pub/Sub.
Experience or knowledge designing scalable, efficient data models for OLAP and OLTP use cases.
Expertise building automated, scalable, and reliable ETL/ELT pipelines using custom Python/Scala solutions or Cloud Data Fusion.
Strong coding skills in Python and SQL; Java/Scala knowledge is optional.
Familiarity with APIs and SDKs for GCP services.
Understanding of GCP services including Cloud Storage, Compute Engine, and Cloud Functions.
Familiarity with Kubernetes (GKE) and containerisation is optional but advantageous.
Experience setting up CI/CD pipelines using Cloud Build, GitHub Actions, or other tools.
Knowledge of Cloud Monitoring and Cloud Logging for production workflows.
Ability to think creatively and design innovative solutions for complex data challenges.
Experience prototyping and experimenting with GCP tools or third-party integrations.
Strong analytical mindset
Ability to collaborate with data analysts and business stakeholders
Strong verbal and written communication skills
Openness to exploring new GCP features and adapting to changes in cloud technology

Responsibilities

Design and implement scalable data engineering solutions using GCP big data technologies.
Build data warehouses and perform SQL analytics with BigQuery.
Run Spark and Hadoop clusters using Dataproc.
Orchestrate data pipelines with Airflow.
Support stream and batch data processing with Dataflow.
Support real-time messaging and event ingestion with Pub/Sub.
Design scalable data models for OLAP and OLTP use cases.
Build automated, scalable, and reliable ETL/ELT pipelines using Python/Scala solutions or Cloud Data Fusion.
Build custom data solutions using GCP APIs and SDKs.
Deploy data pipelines using cloud infrastructure and containerisation.
Set up CI/CD pipelines and monitor production workflows using Cloud Monitoring and Cloud Logging.
Collaborate with data analysts and business stakeholders and communicate technical concepts to non-technical audiences

Skills

GCP Big Data Tools

BigQuery

Dataproc

Airflow

Dataflow

Pub/Sub

Python

SQL

Kubernetes (GKE)

CI/CD

Cloud Monitoring

Cloud Logging

APIs & SDKs (GCP)

Communication skills

Education

Graduate in Computer Science

Tools

Cloud Data Fusion

Cloud Build

GitHub Actions

Docker

Kubernetes (GKE)

Job description

Design and implement scalable data engineering solutions using GCP big data technologies
Build data warehouses and perform SQL analytics with BigQuery
Run Spark and Hadoop clusters using Dataproc
Orchestrate data pipelines with Airflow
Support stream and batch data processing with Dataflow
Support real-time messaging and event ingestion with Pub/Sub
Design scalable data models for OLAP and OLTP use cases
Build automated, scalable, and reliable ETL/ELT pipelines using Python/Scala solutions or Cloud Data Fusion
Build custom data solutions using GCP APIs and SDKs
Deploy data pipelines using cloud infrastructure and containerisation
Set up CI/CD pipelines and monitor production workflows using Cloud Monitoring and Cloud Logging
Collaborate with data analysts and business stakeholders and communicate technical concepts to non-technical audiences

Requirements

Graduate in Computer Science, or related field
6+ years of experience in data engineering or related field
Proficiency in GCP big data tools, including BigQuery, Dataproc, Airflow, Dataflow, and Pub/Sub
Experience or knowledge designing scalable, efficient data models for OLAP and OLTP use cases
Expertise building automated, scalable, and reliable ETL/ELT pipelines using custom Python/Scala solutions or Cloud Data Fusion
Strong coding skills in Python and SQL; Java/Scala knowledge is optional
Familiarity with APIs and SDKs for GCP services
Understanding of GCP services including Cloud Storage, Compute Engine, and Cloud Functions
Familiarity with Kubernetes (GKE) and containerisation is optional but advantageous
Experience setting up CI/CD pipelines using Cloud Build, GitHub Actions, or other tools
Knowledge of Cloud Monitoring and Cloud Logging for production workflows
Ability to think creatively and design innovative solutions for complex data challenges
Experience prototyping and experimenting with GCP tools or third-party integrations
Strong analytical mindset
Ability to collaborate with data analysts and business stakeholders
Strong verbal and written communication skills
Openness to exploring new GCP features and adapting to changes in cloud technology

Core Competencies

Demonstrates expertise in designing and implementing scalable data engineering solutions using GCP big data technologies, with a strong focus on building automated ETL/ELT pipelines and data models for OLAP and OLTP use cases. Proficient in collaborating with stakeholders and communicating complex technical concepts effectively.

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