GCP Senior Data Engineer

We are hiring a GCP Senior Data Engineer

Experience: 7+

Mode:Hybrid

Location: Bangalore

Notice Period: Immediate to 15 Days

Core Responsibilities

1. 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.

2. 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.

3. 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.

4. 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.

• 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).