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

TL;DR

Senior Data Engineer with Google Cloud Spanner and Graph, Graph Platform (Google Cloud Spanner/Graph): Building a unified Spanner-based data platform that combines relational storage, graph modeling, and vector search with an accent on complex graph traversals, near real-time synchronization, and hybrid data access patterns. Focus on designing and optimizing a unified data layer with CDC pipelines, advanced SQL/ISO GQL queries, and scalable ETL/ELT data ingestion.

Location: Remote (Bulgaria, Georgia, Kazakhstan, Poland) or Almaty, Astana, Belgrade, Cluj-Napoca, Dnipro, Kharkiv, Krakow, Kyiv, Larnaca, Lodz, Lublin, Lviv, Odesa, Riga, Sofia, Tbilisi, Varna, Warsaw, Wroclaw, Yerevan

Company

hirify.global builds and delivers technology solutions for clients.

What you will do

• Design and implement Google Cloud Spanner schemas (including interleaved tables) to optimize performance and data locality.
• Collaborate with database and architecture teams to define unified relational and graph data models.
• Develop and optimize advanced SQL and ISO GQL queries for 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/ELT processes for data ingestion and transformation.
• Optimize database performance (query tuning, indexing strategies, workload optimization) and ensure data consistency across representations.

Requirements

• Strong data engineering background with hands-on experience building data platforms.
• Production experience with Google Cloud Spanner.
• Advanced SQL skills (query optimization and performance tuning).
• Experience designing and implementing CDC pipelines and real-time data synchronization.
• Hands-on experience with ETL/ELT and data pipeline architecture; strong Python proficiency for data processing and pipeline development.
• Experience with graph modeling and familiarity with graph query languages such as GQL.

Nice to have

• Experience with vector search technologies and embedding-based retrieval.
• Familiarity with Apache Beam for distributed data processing.
• Experience 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.

Culture & Benefits

• Vacation, sick pay, and time off for state holidays according to the laws and official calendar of your country.
• Health insurance support for you and your loved ones.
• Learning support: coverage of IT certification costs and access to courses and learning platforms.
• Flexible work on global projects with a supportive tech environment.
• Time off for state holidays regardless of the client’s schedule.

Hiring process

• Apply and go through recruiter screening.
• Interviews to evaluate technical fit for data engineering, Spanner/graph, and pipeline design.
• Final discussions to confirm alignment on scope and expectations.