GCP Data Engineer

EXL

GCP Data Engineer building scalable GCP data pipelines and models for enterprise analytics. Developing ETL/ELT workflows, CI/CD, and cloud data solutions.

Posted 9/10/2026full-timeGurugram • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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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.

Highest-signal resume keywords

GCP Big Data ToolsETL/ELT Pipeline DevelopmentSQL Analytics with BigQueryData Pipeline Orchestration with AirflowCloud Monitoring and Logging

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSQLPythonScalaBigQueryDataprocAirflowDataflowCloud Data FusionGCP APIs and SDKs

Soft Skills

Analytical MindsetCreative Problem SolvingCollaborationVerbal CommunicationWritten Communication

Tools & Technologies

Cloud StorageCompute EngineCloud FunctionsKubernetes (GKE)Cloud BuildGitHub Actions

Industry Keywords

OLAPOLTPCI/CD PipelinesEvent IngestionReal-Time Messaging

Tech Stack

Tools & technologies

AirflowBigQueryCloudETLGoogle Cloud PlatformHadoopJavaKubernetesPythonScalaSparkSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Benefits

Comp & perks

No benefits, perks, or compensation extras are specified