Senior Data Engineer with Google Cloud Spanner and Graph, Graph Platform

Senior Data Engineer with Google Cloud Spanner and Graph, Graph Platform

Data

This project focuses on building a unified Spanner based data platform that combines relational storage, graph modeling, and vector search to enable hybrid data access patterns. The solution supports complex graph traversals and near real time synchronization across multiple data representations.

Position overview

We are looking for a Senior Data Engineer with strong experience in Google Cloud Spanner and graph technologies to contribute to a high performance data platform. You will work at the intersection of relational, vector, and graph data models, helping to design and optimize a unified data layer that supports advanced analytics and real time retrieval.

Google Cloud Platform, Cloud Spanner, BigQuery, Pub Sub, Dataflow, SQL, ISO GQL, Python, Apache Beam, CDC pipelines, ETL and ELT frameworks, graph databases, vector search technologies, IAM, encryption

Responsibilities

Design and implement Cloud Spanner schemas including interleaved table structures to optimize performance and data locality

Collaborate with the database and architecture teams to define unified relational and graph data models

Develop and optimize advanced SQL and ISO GQL queries to support efficient graph traversals and hybrid access patterns

Build and maintain CDC pipelines to synchronize relational, graph, and vector data in near real time

Design and implement ETL and ELT processes to support data ingestion and transformation

Optimize database performance through query tuning, indexing strategies, and workload optimization

Implement graph modeling approaches to represent complex relationships and enable advanced querying

Support vector search capabilities integrated with graph and relational data layers

Ensure data consistency, correctness, and synchronization across all data representations

Collaborate with cross functional teams to deliver scalable, reliable, and observable data pipelines

Requirements

Strong data engineering background with hands on experience in building data platforms

Experience working with Google Cloud Spanner in production environments

Advanced SQL skills including query optimization and performance tuning

Experience designing and implementing CDC pipelines and real time data synchronization

Hands on experience with ETL and ELT processes and data pipeline architecture

Proficiency in Python for data processing and pipeline development

Experience with graph modeling and familiarity with graph query languages such as GQL

Understanding of distributed data systems and scalable architecture patterns

Familiarity with Google Cloud Platform services such as BigQuery, Pub Sub, and Dataflow

Knowledge of data governance concepts including data quality, lineage, and consistency

Understanding of data security practices including IAM and encryption standards

Nice to have

Experience with vector search technologies and embedding based retrieval

Familiarity with Apache Beam for distributed data processing

Experience working with hybrid architectures combining relational, graph, and vector data

Exposure to AI driven data platforms or machine learning pipelines

Experience with observability tools for monitoring data pipelines and system performance

What We Offer:

Vacation days : Up to 26 business days per year.

10 illness/special days off per year (fully paid, no medical papers needed) for all contract types

Health and life insurance (Luxmed)

MyBenefit platform with Multisport option

Internal psychological support service

English language classes from the first working day

Access to external learning platforms : O’Reilly, LinkedIn Learning, Udemy, and a wide catalog of diverse internal training

Flexible workplace : work from the office, from home, or choose a hybrid option

Opportunities to develop as a public speaker, mentor, or technical interviewer

Fully paid idle (bench) when not involved in a project