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

- Solid 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

📌 GCP Data Engineer (Bengaluru)
🏢 TEKnuova
📍 Bengaluru