FULL STACK GCP DATA ENGINEER

Responsibilities

Heres how youll contribute:

You will contribute to the role by:

• Creating Impact faster: Delivering more Impact In less time by quickly deploying solutions or augmenting existing ones to enable teams to accelerate business results and Increase time to value
• Breaking through barriers: Helping create better customer experience by taking the data first approach and deliver Insights
• Adapting to anything: Agility to reacting and responding to new business priorities and market conditions and customer opportunities with rapidly deployable solutions
• Innovating anywhere: Solving problems with powerful solutions enabling Inter operable solutions across multiple lines of business

Skills required to contribute

• 6-9 Years of Data Engineering experience on Google Cloud Platform (GCP), including hands-on delivery in BigQuery-based data platforms and working exposure to Agentic AI development.
• Hands-on expertise in Google BigQuery, including writing and optimizing complex SQL queries for large-scale, structured and semi-structured data warehousing and analytics.
• Strong SQL skills and solid data engineering fundamentals, including data modelling, ETL/ELT design, and data quality and validation practices.
• Ability to understand, trace and debug end-to-end data pipeline flows, quickly identifying and resolving data quality, processing and orchestration issues.
• Awareness of performance optimization techniques for BigQuery and GCP data pipelines, including query tuning, partitioning, clustering, slot management and cost optimization.
• Familiarity with change management processes and best practices for controlled, governed releases into production data environments.
• Experience with CI/CD and DevOps practices for data engineering, including version control (Git), automated testing and deployment pipelines on GCP.
• Working knowledge of BI dashboarding tools (e.g., Looker, Power BI, Tableau, Google Looker Studio) and basic AI/ML concepts to support analytics, reporting and predictive use cases.
• Ability to produce and explain a Blueprint Architecture Diagram / data flow diagram, articulating end-to-end solution design to both technical and business stakeholders.
• Hands-on proficiency running and troubleshooting commands using SQL, bq, gcloud and gsutil in a production GCP environment.
• Hands-on experience with Agentic AI development, preferably within the GCP ecosystem (e.g., Vertex AI Agent Builder, Gemini-based or LangChain/LangGraph agents), building AI-driven automation to accelerate data engineering delivery.
• Full-stack data engineering exposure - comfortable working across ingestion, transformation, orchestration (e.g., Cloud Composer/Airflow) and consumption layers within a GCP-based data platform.
• Excellent communication, stakeholder management and presentation skills, with experience operating in a blended onshore/offshore delivery model.
• Professional Google Cloud certification (e.g., Professional Data Engineer) will be an added advantage.
• Nice to have: Experience with Python, Snowflake, Databricks or other cloud data platforms, and prior exposure to retail / large-scale enterprise data environments.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.