Data Engineer

Teknuova; Gurugram District, Bengaluru, Mumbai; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

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

You will work with BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and related GCP services to ingest, transform, and model data, while emphasizing data quality, security, and cost-efficient

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.
• 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.

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.

Skills

Google Cloud Platform

BigQuery

Python

SQL

ETL/ELT pipelines

Data warehousing

Apache Beam

Git version control

CI/CD

Spark

Tools

Dataflow

Dataproc

Cloud Composer

Pub/Sub

Cloud Storage

Terraform

Docker

Kubernetes

Apache Airflow

dbt

Git

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