Google Cloud Platform Data Engineer (Seniors Experts atleast 14years plus)

We are seeking a hands-on Google Cloud Platform BigQuery Graph Engineer for a short-term retail client engagement. The consultant will work with large-scale data in Google Cloud Platform, leveraging BigQuery and graph-based data modeling/analytics to identify, model, and analyze relationships across complex datasets.

This role requires strong hands-on engineering capabilities and the ability to quickly understand existing data structures, translate business use cases into graph-oriented data models, and develop scalable solutions within the Google Cloud Platform ecosystem.

Key Responsibilities

• Design and develop graph-oriented data models and solutions using data housed within Google BigQuery.
• Analyze complex relationships across large retail datasets, including customer, product, transaction, behavioral, and other interconnected data.
• Build and optimize BigQuery SQL queries, transformations, and data structures to support graph analytics and downstream applications.
• Develop approaches for representing entities, nodes, edges, relationships, and paths from structured and semi-structured datasets.
• Integrate BigQuery data with appropriate graph technologies, libraries, or Google Cloud Platform services as required by the solution.
• Partner with architects, data engineers, data scientists, and business stakeholders to translate use cases into technical solutions.
• Perform data profiling, entity mapping, relationship discovery, and data-quality validation.
• Optimize solutions for performance and scalability across large datasets.
• Rapidly assess the client's existing environment and deliver working solutions within a short 4 6 week engagement.
• Document architecture, data models, technical decisions, and implementation recommendations.

Required Qualifications

• Strong hands-on experience with Google Cloud Platform (Google Cloud Platform).
• Advanced experience with Google BigQuery, including complex SQL, data modeling, query optimization, and large-scale data processing.
• Experience with graph data modeling, graph analytics, knowledge graphs, or graph databases.
• Strong understanding of graph concepts including nodes, edges, entities, relationships, traversal, and relationship modeling.
• Experience transforming relational or analytical datasets into graph-oriented structures.
• Strong SQL skills and proficiency with Python for data engineering and/or graph processing.
• Experience designing and implementing scalable cloud-based data solutions.
• Ability to work independently and deliver quickly within a short-duration project.
• Strong communication skills with the ability to translate business requirements into technical implementation.

Preferred Qualifications

• Experience working with retail, consumer, customer, product, or transactional datasets.
• Experience with graph technologies such as Neo4j, NetworkX, TigerGraph, Neptune, or similar graph platforms/frameworks.
• Experience with additional Google Cloud Platform data services such as Cloud Storage, Dataflow, Dataproc, Pub/Sub, Vertex AI, or Looker.
• Experience with customer 360, recommendation, personalization, product relationships, identity resolution, fraud/network analysis, or similar graph-based use cases.
• Experience working in consulting or fast-paced client delivery environments.