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About the Role

The Lead Data Virtualisation Engineer will lead the design, deployment, and adoption of the Starburst data analytics platform for the organization’s first implementation. This role requires deep technical experience in distributed SQL engines and data lakes, along with the ability to guide stakeholders through platform onboarding and production readiness. The role involves creating unified, real-time views of data from multiple sources to enable AI and users to access and integrate data for analytics, reporting, and business intelligence. This includes a research and development component, collaborating with the vendor to refine the product.

Responsibilities

Lead end-to-end implementation of Starburst (Trino-based) platform from initial setup through production rollout
Serve as the Starburst subject matter expert, providing guidance and technical leadership
Design and implement scalable query architecture across data lakes, warehouses, and enterprise data sources
Deploy and configure Starburst Enterprise, including Trino cluster setup and tuning
Integrate multiple data sources i.e. Snowflake, databases, etc.
Implement security, authentication, and authorization aligned with enterprise standards
Optimize query performance, concurrency, and resource utilization
Establish monitoring, alerting, and operational best practices
Collaborate with cloud and platform teams to ensure high availability, scalability, and reliability
Prepare relevant documentation
Speed up adoption of AI
Improve data governance
Improve time-to-market of data products

Requirements

10+ years of experience in data engineering, analytics platforms, or distributed systems
Hands-on experience with Starburst, Trino, or Presto
Strong background in cloud engineering (AWS/Azure/GCP) and Kubernetes
Proficiency in SQL, data lakes, object storage, and distributed query optimisation
Good understanding of data security, governance, and access controls
Prior experience leading first-time platform implementations
Experience migrating to Starburst
Familiarity with BI, data engineering, enterprise analytics use cases (Power BI, dbt, Python, Spark)
Strong communication and stakeholder management skills

Skills

Technical leadership and ownership
Architecture and problem-solving mindset
Ability to work independently in ambiguous environments
Strong documentation and knowledge-sharing skills
Strong understanding of AI fundamentals, Large Language Models (LLMs), and agentic AI architectures
Ability to leverage modern data platforms, governance, and data products to enable successful AI outcomes
Excellent communication skills
Results driven, with a strong sense of accountability
A proactive, motivated approach
The ability to operate with urgency and prioritise work accordingly
Strong decision-making skills, the ability to demonstrate sound judgement
A structured and logical approach to work
Strong problem-solving skills
A creative and innovative approach to work
Excellent interpersonal skills
The ability to manage large workloads and tight deadlines
Excellent attention to detail and accuracy
A calm approach, with the ability to perform well in a pressurised environment
Strong numerical skills

Experience Level

10+ years of experience

Education Level

Bachelor’s degree in computer science, Engineering, or related field, or equivalent experience
Cloud certifications (Azure/AWS/GCP)

About the Company

Mitsubishi UFJ Financial Group (MUFG) is one of the world’s leading financial groups with 150,000 colleagues globally.
The company strives to make a difference for every client, organization, and community it serves.
MUFG stands for its values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.
The company's vision is to be the world’s most trusted financial group.
It is part of MUFG's culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility.
MUFG invests in talent, technologies, and tools that empower employees to own their careers.
The Data Fabric team is part of the Data Engineering & Business Intelligence (DEBI) Department, within the Architecture, Middleware, Data Engineering & Business Intelligence (AMD) pillar of Technology.
Data Fabric is responsible for designing and developing enterprise-grade solutions that support Data Virtualisation.

Equal Opportunity

MUFG is committed to embracing diversity and building an inclusive culture where all employees are valued, respected and their opinions count.
The company supports the principles of equality, diversity and inclusion in recruitment and employment, and opposes all forms of discrimination on the grounds of age, sex, gender, sexual orientation, disability, pregnancy and maternity, race, gender reassignment, religion or belief and marriage or civil partnership.
Recruitment decisions are made in a non-discriminatory manner in accordance with the commitment to identifying the right skills for the right role and legal obligations.