Lead BigQuery / Graph DBA – GCP & Neo4j Specialist at Hitachi Vantara Corporation

, , India -

Full Time

Start Date

Immediate

Expiry Date

30 Apr, 26

Salary

0.0

Posted On

30 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

BigQuery, Neo4j, Graph Databases, Data Modeling, SQL, Cypher, ETL, Data Governance, Cloud Security, AI Integration, Knowledge Graphs, Performance Optimization, Data Architecture, Disaster Recovery, Data Ingestion, Analytical Skills

Industry

IT Services and IT Consulting

Description

About Us: Hitachi Digital is building next-generation data platforms to power AI-driven insights and enterprise-scale analytics. We leverage Google Cloud Platform (GCP) and graph technologies to deliver secure, scalable, and intelligent data ecosystems. We are seeking a Lead BigQuery / Graph DBA with deep expertise in BigQuery, Neo4j, and graph-based data modeling to design and optimize high-performance data architectures. Role Overview As a Lead BigQuery / Graph DBA, you will architect, manage, and optimize cloud-native data warehouses and graph databases. You will lead data modeling, query optimization, and integration strategies for structured and graph-based data, enabling advanced analytics and AI workflows across global OpCos. Key Responsibilities Database Architecture & Management Design and maintain BigQuery data warehouses for large-scale analytics. Develop graph schemas, relationships, and knowledge graphs using Neo4j. Implement data ingestion pipelines, ETL processes, and partitioning strategies for performance optimization. Performance & Optimization Optimize SQL queries, Cypher queries, and indexing for high-volume datasets. Monitor and tune BigQuery cost-performance and Neo4j Ensure high availability, disaster recovery, and backup strategies for critical data assets. Integration & AI Enablement Integrate graph databases with AI/ML pipelines for semantic search and contextual reasoning. Enable RAG workflows and knowledge graph-driven AI for enterprise applications. Collaborate with data engineering and AI teams to embed graph intelligence into analytics platforms. Governance & Security Enforce data governance policies, lineage tracking, and compliance standards. Implement IAM roles, VPC-SC, and data protection controls on GCP. Document architecture decisions, query patterns, and best practices. Required Qualifications Bachelor’s or Master’s in Computer Science, Data Engineering, or related field. 8+ years in database administration; 3+ years with BigQuery and Neo4j. Strong proficiency in SQL, Cypher, and data modeling for relational and graph databases. Hands-on experience with GCP services (BigQuery, IAM, VPC-SC, Cloud Storage). Familiarity with graph algorithms, knowledge graphs, and semantic modeling. Understanding of ETL pipelines, data governance, and cloud security. Preferred Qualifications Certifications: Google Professional Data Engineer, Neo4j Certified Professional. Experience with AI/ML integration, RAG pipelines, and agentic workflows. Exposure to Looker BI, Power BI, or Tableau for visualization. Knowledge of LangChain, vector databases, and embedding strategies. Key Competencies Strong analytical and problem-solving skills. Ability to design scalable, secure, and performant data architectures. Collaborative mindset with excellent communication skills. Passion for graph-driven AI and cloud-native data platforms. Success Metrics Deployment of optimized BigQuery and Neo4j environments for enterprise analytics. Integration of knowledge graphs into AI workflows for contextual intelligence. Reduction in query latency and cost across large-scale datasets. Positive impact on data quality, governance, and compliance readiness. What You’ll Work With Cloud & Data: GCP BigQuery, Cloud Storage, IAM, VPC-SC. Graph DB: Neo4j, Cypher, APOC procedures. AI Integration: Knowledge Graph + LLM workflows, RAG pipelines. Tools: Python, SQL, ETL frameworks, BI tools (Looker preferred). #LI-MS3 About us We’re a global, 1000-stong, diverse team of professional experts, promoting and delivering Social Innovation through our One Hitachi initiative (OT x IT x Product) and working on projects that have a real-world impact. We’re curious, passionate and empowered, blending our legacy of 110 years of innovation with our shaping our future. Here you’re not just another employee; you’re part of a tradition of excellence and a community working towards creating a digital future. Fostering innovation through diverse perspectives Hitachi is a global company operating across a wide range of industries and regions. One of the things that sets Hitachi apart is the diversity of our business and people, which drives our innovation and growth. We are committed to building an inclusive culture based on mutual respect and merit-based systems. We believe that when people feel valued, heard, and safe to express themselves, they do their best work. How we look after you We help take care of your today and tomorrow with industry-leading benefits, support, and services that look after your holistic health and wellbeing. We’re also champions of life balance and offer flexible arrangements that work for you (role and location dependent). We’re always looking for new ways of working that bring out our best, which leads to unexpected ideas. So here, you’ll experience a sense of belonging, and discover autonomy, freedom, and ownership as you work alongside talented people you enjoy sharing knowledge with. We’re proud to say we’re an equal opportunity employer and welcome all applicants for employment without attention to race, colour, religion, sex, sexual orientation, gender identity, national origin, veteran, age, disability status or any other protected characteristic. Should you need reasonable accommodations during the recruitment process, please let us know so that we can do our best to set you up for success.

Responsibilities

The Lead BigQuery / Graph DBA will architect, manage, and optimize cloud-native data warehouses and graph databases. This role involves leading data modeling, query optimization, and integration strategies for structured and graph-based data.