招聘
Data Engineer (Graph, Vector & Data Platform) - Senior Associate, AI & Data, Technology Consulting

Data Engineer (Graph, Vector & Data Platform) - Senior Associate, AI & Data, Technology Consulting
·
On-site
·
Full-time
·
1mo ago
必备技能
SQL
Go
At EY, we develop you with future-focused skills and equip you with world-class experiences. We empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams.
We work together across our full spectrum of services and skills powered by technology and AI, so that businesses, people and the planet can thrive together.
We’re all in, are you?
Join EY and shape your future with confidence.
About the opportunity
EY AI & Data is the data and advanced analytics capability within EY Asia-Pacific, with over 500 specialist employees working across multiple industry sectors. We implement information-driven strategies, data platforms, and advanced data analytics solution systems that help grow, optimize, and protect client organizations. We go beyond strategy and provide end to end design, build and implementation of real-life data environments and have some of the best architects, project managers, business analysts, data scientists, big data engineers, developers and consultants in the region.
We are seeking a Data Engineer with strong experience in graph databases, entity network analysis, and vector data platforms to design, build, and operate scalable data solutions. The role focuses on Neo4j-based graph platforms, vector databases, and modern data repositories using Apache Iceberg, running on Nutanix hybrid infrastructure, to support advanced analytics, AI, and enterprise data use cases.
Your key responsibilities
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Design and implement graph data models and entity networks using Neo4j
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Develop and optimize Cypher queries for relationship and network analysis
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Build and maintain vector databases using Postgres (pgvector), Milvus, or Weaviate
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Implement embedding ingestion pipelines for similarity and semantic search use cases
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Design and manage data repositories / lakehouse layers using Apache Iceberg
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Develop data ingestion and transformation pipelines from multiple source system
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Deploy and operate databases and data platforms on Nutanix infrastructure
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Ensure performance tuning, scalability, availability, and fault tolerance
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Implement data quality checks, monitoring, and error handling
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Collaborate with AI/ML, analytics, and application teams
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Document data models, architectures, and operational procedures
To qualify for the role, you must have
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Bachelor's degree in computer science, Information Systems, or related field.
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Minimally 4 years of hands-on experience in Data Engineering
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Strong hands-on experience with Neo4j (Graph DB)
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Proven experience in entity network analysis and relationship-based modeling
Hands-on experience with vector databases:
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Postgres (pgvector), Milvus, and/or Weaviate
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Strong SQL skills and experience with complex data transformations
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Experience designing data lakes / lakehouse architectures
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Hands-on experience with Apache Iceberg or similar table formats
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Experience operating data platforms on Nutanix or comparable on-prem / hybrid infrastructure
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Solid understanding of distributed systems and data storage concepts
Ideally, you’ll also have
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Python or Java for data processing and integration
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Experience with Spark, Kafka, or Flink
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Experience with LLM / AI pipelines and embedding generation
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Knowledge of Elasticsearch or hybrid search architectures
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Experience with data governance, security, and access control
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Exposure to DevOps / CI-CD for data platforms
What we look for
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Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry.
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An effective communicator, you’ll be a confident leader equipped with strong people management skills and a genuine passion to make things happen in a dynamic organization.
What working at EY offers
EY offers a competitive remuneration package where you’ll be rewarded for your individual and team performance. We are committed to being an inclusive employer and are happy to consider flexible working arrangements. Plus, we offer:
Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next.
Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs.
Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.
Company description
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
All in to shape the future with confidence.
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关于EY

EY
PublicEY, previously known as Ernst & Young, is a British multinational professional services network based in London, United Kingdom. Along with Deloitte, KPMG and PwC, it is one of the Big Four professional services firms.
10,001+
员工数
London
总部位置
评价
3.4
10条评价
工作生活平衡
2.3
薪酬
3.8
企业文化
3.7
职业发展
3.5
管理层
3.2
65%
推荐给朋友
优点
Good learning opportunities and career advancement
Supportive culture and kind people
Great benefits and compensation
缺点
Long hours and poor work-life balance
Brutal and taxing work environment during busy periods
Limited support for interns and technical growth
薪资范围
31,254个数据点
Mid/L4
Mid/L4 · Operations Research Analyst
1,738份报告
$142,571
年薪总额
基本工资
$136,899
股票
-
奖金
$5,673
$100,128
$203,912
面试经验
7次面试
难度
3.0
/ 5
时长
14-28周
录用率
57%
面试流程
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
Technical/Case Interview
5
Partner/Director Interview
6
Offer
常见问题
Behavioral/STAR
Case Study
Technical Knowledge
Past Experience
Culture Fit