Data Engineer

2 days ago

Coimbatore, Tamil Nadu, India ShellKode Full time ₹ 15,00,000 - ₹ 20,00,000 per year

Role Overview
We are seeking a skilled Data Engineer with 3+ years of hands-on experience in building and managing data pipelines, data models, and cloud-based analytics solutions on
Google Cloud Platform (GCP)
. The ideal candidate will have strong expertise in GCP-native services such as
BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Composer
, along with proven experience in SQL, Python, and ETL/ELT design.

This role requires working closely with data scientists, analysts, and business teams to ensure scalable, reliable, and high-performance data infrastructure.

Key Responsibilities

  • Data Pipeline Development

  • Design, build, and optimize scalable ETL/ELT pipelines using GCP services (Dataflow, Composer, Pub/Sub, BigQuery).

  • Ingest structured and unstructured data from multiple sources into cloud storage and warehouse solutions.

  • Data Warehousing & Modeling

  • Develop efficient and optimized data models in BigQuery.

  • Implement partitioning, clustering, and query optimization for performance and cost efficiency.

  • Cloud Infrastructure

  • Work with GCP-native tools for data integration, storage, and analytics.

  • Ensure high availability, security, and compliance of data systems.

  • Collaboration & Support

  • Partner with data scientists, analysts, and application teams to deliver reliable datasets.

  • Troubleshoot issues, monitor pipelines, and ensure SLAs for data delivery.

  • Best Practices & Governance

  • Implement data quality checks, monitoring, and lineage tracking.

  • Follow DevOps and CI/CD practices for data engineering projects.

Required Skills & Qualifications

  • 3+ years of hands-on experience in data engineering.

  • Strong expertise in GCP data services:

  • BigQuery (SQL, performance tuning, cost optimization)

  • Dataflow (Apache Beam pipelines)
  • Cloud Composer (Airflow orchestration)
  • Pub/Sub (streaming ingestion)

  • Cloud Storage, Dataproc

  • Proficiency in SQL and Python for data transformation and automation.

  • Good knowledge of ETL/ELT design, data modeling, and warehousing principles.
  • Experience with Git, CI/CD pipelines, and version control.
  • Understanding of data security, IAM, and compliance in cloud environments.

Nice-to-Have Skills

  • Familiarity with Terraform/Deployment Manager for IaC (Infrastructure as Code).
  • Knowledge of Kafka, Spark, or DBT for advanced data engineering use cases.

Skills: gcp,pipelines,data,data engineering

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