FULL STACK GCP DATA ENGINEER

Here's how you'll contribute:

• 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.