GCP Data Engineer

Teknuova

Gurugram District, Bengaluru, Mumbai

Hybrid

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

Full time

3 days ago
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Job summary

Teknuova is seeking a Data Engineer to design, build, and maintain scalable data pipelines on Google Cloud Platform. You will work with cross-functional teams to ensure data reliability and accessibility for downstream use cases.

Responsibilities include developing ETL/ELT pipelines with Dataflow, Dataproc, Cloud Composer, and Pub/Sub, using BigQuery for data modeling and optimization, and maintaining data storage in Cloud Storage. Strong Python and SQL skills are essential.

Qualifications

  • Strong hands-on experience with Google Cloud Platform.
  • Experience with BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
  • Strong programming skills in Python.
  • Strong proficiency in SQL.
  • Experience designing and building ETL/ELT pipelines.
  • Knowledge of data warehousing, data modeling, and distributed processing.
  • Experience with large-scale structured and unstructured datasets.
  • Knowledge of Apache Beam or Spark frameworks.
  • Familiarity with Git/version control.
  • Strong problem-solving and debugging skills.

Responsibilities

  • Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP).
  • Build and manage batch and real-time data processing workflows.
  • Develop data ingestion, transformation, and integration across sources.
  • Work with BigQuery to design data models and optimize queries.
  • Build ETL/ELT pipelines using Dataflow, Dataproc, Cloud Composer, and Pub/Sub.
  • Manage and process data stored in Google Cloud Storage.
  • Ensure data quality, security, and reliability across platforms.
  • Monitor and troubleshoot data pipelines and production workflows.
  • Optimize cloud infrastructure and data processing workloads for performance and cost.
  • Collaborate with data scientists, analysts, software engineers, and stakeholders.
  • Implement CI/CD and automation for data workflows.
  • Maintain detailed documentation for pipelines and architecture.

Skills

Google Cloud Platform
BigQuery
Cloud Storage
Dataflow
Dataproc
Pub/Sub
Cloud Composer
Python
SQL
ETL/ELT Pipelines
Data warehousing
Data modeling
Apache Beam
Spark
Git

Tools

Apache Airflow
Terraform
Docker
Kubernetes
dbt
Kafka

Job description

We are looking for a Data Engineer to design, build, and maintain scalable data pipelines and cloud-based data platforms on Google Cloud Platform. You will work with engineering, analytics, and business teams to ensure data is reliable, accessible, and optimized for downstream use cases.


Key Responsibilities
  • Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP)
  • Build and manage batch and real-time data processing workflows
  • Develop data ingestion, transformation, and integration solutions across multiple data sources
  • Work with BigQuery to design data models, optimize queries, and improve data warehouse performance
  • Build ETL/ELT pipelines using services such as Dataflow, Dataproc, Cloud Composer, and Pub/Sub
  • Manage and process data stored in Google Cloud Storage
  • Ensure data quality, consistency, security, and reliability across data platforms
  • Monitor and troubleshoot data pipelines and production workflows
  • Optimize cloud infrastructure and data processing workloads for performance and cost
  • Collaborate with data scientists, analysts, software engineers, and business stakeholders
  • Implement CI/CD and automation practices for data engineering workflows
  • Maintain technical documentation for data pipelines, architecture, and processes
Required Skills
  • Strong hands-on experience with Google Cloud Platform
  • Experience with BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Cloud Composer
  • Strong programming skills in Python
  • Strong proficiency in SQL
  • Experience designing and building ETL/ELT pipelines
  • Good understanding of data warehousing, data modeling, and distributed data processing
  • Experience working with large-scale structured and unstructured datasets
  • Knowledge of Apache Beam, Spark, or similar data processing frameworks
  • Familiarity with Git and version control
  • Strong problem-solving and debugging skills
Good to Have
  • Experience with Apache Airflow
  • Knowledge of Terraform or Infrastructure as Code
  • Experience with Docker and Kubernetes
  • Familiarity with Kafka or other streaming technologies
  • Exposure to dbt
  • Experience implementing data governance and data security practices
  • Knowledge of GCP IAM, networking, and cloud security
  • Google Cloud certification such as Professional Data Engineer

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