Company: krtrimaIQ Cognitive Solutions

Job type: Full-time

Location: Remote

Experience : 8+ years of relevant experience in data engineering, cloud data platforms, or related fields. Candidates should demonstrate a proven track record of designing and implementing production-grade data pipelines on Google Cloud Platform, optimizing complex data solutions, and working effectively in collaborative technical environments. About the company:

KrtrimaIQ is a forward-thinking technology company specializing in cloud-based data solutions and intelligent data engineering practices. We empower organizations to harness the full potential of their data through scalable, reliable, and innovative platforms built on modern cloud infrastructure. Our team is composed of experienced data engineers, architects, and technical leaders who are passionate about solving complex data challenges.

We work with enterprise clients across diverse industries, delivering production-grade data pipelines and analytics solutions that drive business intelligence and operational excellence.

Responsibilities

Design and develop scalable ETL/ELT pipelines using Dataflow (Java/Apache Beam), and Cloud Composer (Airflow) to reliably process and transform data at scale

Build and optimize large-scale data warehousing solutions in BigQuery, including partitioning, clustering, and query performance tuning

Develop and maintain SQL-based transformation workflows using Dataform, applying sound data modeling practices for analytics-ready datasets

Optimize data pipeline performance and cost-effectiveness across GCP services,



including efficient use of BigQuery slots, Dataflow autoscaling

Architect and implement data solutions using GCP-native services such as Cloud Storage, Pub/Sub, Cloud Functions, Cloud Composer, and Dataform, following cloud engineering best practices

Troubleshoot and resolve complex data pipeline issues across the GCP data stack, implementing systematic and repeatable solutions

Collaborate with analytics teams, data scientists, and business stakeholders to understand requirements and deliver solutions on GCP

Establish and maintain data quality standards, implementing validation and monitoring mechanisms using tools like Cloud Monitoring, Cloud Logging, and Dataplex

Leverage AI-assisted development tools to accelerate pipeline development, improve code quality, and streamline debugging

Lead technical design discussions and mentor junior team members on GCP data engineering best practices

Participate in code reviews and drive continuous improvement of data engineering processes, including CI/CD for GCP-based pipelines

Mentor other data engineers on the team

Skills

Design and Development of large scale data engineering pipelines on GCP with its native data engineering skills





Expert proficiency with BigQuery for large-scale data warehousing, analytics, and query optimization

Advanced hands-on experience with Java/Google Dataflow (Apache Beam) for building and managing streaming and batch data processing pipelines

Strong Hands-on experience with Google Dataform for SQL-based data transformation and modeling within BigQuery

Working knowledge of Cloud Composer (Airflow) for orchestration and workflow scheduling

Familiarity with Pub/Sub for real-time messaging and event-driven pipelines, and Cloud Storage for data lake architecture

Advanced Python and Java programming for data pipeline development and automation

Robust SQL skills for complex data transformations and query optimization within BigQuery

Strong SQL experience with advanced features like window functions, advanced joins, stored procedures, CTEs, Temp Tables, Conditional Pivoting etc.

Familiarity with data modeling concepts (dimensional modeling, star/snowflake schemas) for analytics-ready data design

Experience with AI-assisted development (e.g., Copilot, Claude, Gemini Code Assist) to accelerate pipeline development and code quality

Proficiency with CI/CD practices (e.g., Cloud Build, GitHub Actions) for automated testing and deployment of GCP data solutions

Working knowledge of containerization (Docker, GKE/Cloud Run) for packaging and deploying data applications

Exposure to IAM, VPC Service Controls, and data governance practices within GCP is a plus

📌 Senior GCP Data Engineer (Bengaluru)
🏢 krtrimaIQ Cognitive Solutions
📍 Bengaluru