GCP Senior Data Engineer

Title: GCP Senior Data Engineer

Location: Bangalore / Chennai

Position Summary

The GCP Senior Data Engineer is responsible for designing, building, optimizing, and maintaining

highquality data pipelines and cloudnative data platforms on Google Cloud Platform (GCP). This

role partners closely with data analysts, data scientists, business teams, DevOps, and platform

engineering to deliver secure, reliable, and scalable data solutions that support Trane Technologies

digital strategy.

This position requires strong handson engineering capabilities, cloud experience, and a passion for

delivering enterprisegrade data solutions.

Core Responsibilities

• Data Engineering & Cloud Development (Core Responsibilities) Design, build, and maintain scalable data processing systems on Google Cloud Platform (GCP). Develop endtoend data pipelines to support ingestion, transformation, and storage. Build ELT/ETL workflows, database objects, and cloudnative data orchestration solutions. Optimize pipelines for performance, scalability, cost efficiency, and reliability. Ensure robust monitoring, alerting, and data quality assurance across distributed systems. Implement secure data architectures following Trane Technologies standards.
• Collaboration & Analytics Enablement Work closely with data analysts and data scientists to understand business requirements and translate them into scalable data solutions. Support analytical use cases, data modelling, and enable selfservice data consumption. Partner across global teams, including business stakeholders, product owners, and data governance.
• DevOps / Platform Engineering Partnership Partner with DevOps and platform engineering teams to ensure data infrastructure is secure, reliable, and highly available. Apply working knowledge of CI/CD practices (code versioning, automation, testing frameworks) to support cloudbased deployments. Collaborate on environments, pipelines, and promote code through dev test prod.
• Engineering Excellence & Ways of Working Participate in code reviews and maintain global coding standards. Follow structured engineering methods, documentation practices, and release processes. Contribute effectively in distributed, agile development teams across multiple time zones. Communicate clearly with both technical and nontechnical stakeholders.
• Innovation & Continuous Improvement Research, evaluate, and propose new tools, technologies, and design patterns. Stay current with cloud, data engineering, and analytics trends relevant to enterprisescale environments. Apply continuous improvement practices to enhance reliability, quality, and developer productivity.
  
  

Qualifications

Education Requirements

Bachelor s /Master s degree in Computer Science, Information Technology, Data Engineering,

Software Engineering, or a related technical field.

Experience Requirements

7+ years of total experience in data engineering, data platforms, or datacentric software

engineering.

5+ years of handson experience designing and building data pipelines, ETL/ELT workflows, and

cloudnative data solutions.

3+ years of direct experience with Google Cloud Platform (GCP) using services such as BigQuery,

Cloud Storage, Cloud Run, Datafusion, Dataproc, Composer, and Pub/Sub.

Advanced proficiency in SQL, Python, and PySpark for data processing and transformation.

Proven experience developing and supporting productiongrade, endtoend cloud data pipelines.

Expertise in ELT/ETL design, performance optimization, and data transformation frameworks.

Strong background in monitoring, logging, alerting, and data quality frameworks across distributed

systems.

Experience with DevOps tools and techniques, including CI/CD, GitHub, and related automation

practices.

Demonstrated experience working in global, crossfunctional, and agile development environments.

Excellent communication, problemsolving, and analytical skills with the ability to collaborate across

technical and nontechnical teams.

GCP certification preferred (e.g., Google Cloud Professional Data Engineer).