Senior Consultant / Manager (Data Engineering Lead) - Engineering, AI&Data(107113)

Leadingnation; Hong Kong; On-site; HKD 1,200,000 - 1,800,000; Full time

Job summary

Deloitte China is seeking a Data Engineering Lead to architect and deliver robust data platforms powering AI solutions. You will bridge data infrastructure with high-level AI strategy while leading a team of engineers to deliver measurable business value.

You will guide data governance, security, and performance tuning, collaborating with onshore and offshore teams to ensure delivery excellence and client impact.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related fields.
• 5–8+ years of data engineering experience, with leadership or senior architectural exposure.
• Deep experience with Spark (Batch and Structured Streaming), Kafka, or Flink for distributed data processing.
• Strong proficiency in at least one cloud provider (Databricks, AWS Glue/Lambda, Azure Data Factory, GCP Dataflow).
• Advanced skills in Python and SQL; Scala/Java a plus.
• Solid experience with DevOps and DataOps tooling and practices.

Responsibilities

• Provide technical leadership in designing and implementing scalable data platforms and pipelines.
• Lead and mentor a team of Data Engineers, conducting code reviews and providing career guidance.
• Drive engineering standards for CI/CD, data quality frameworks, automated testing, and DataOps practices.
• Ensure delivery excellence with data governance, security, and quality controls.
• Diagnose and resolve production issues, data corruption, performance bottlenecks across cloud environments.
• Tune Spark jobs and Databricks/BigQuery configurations to improve latency and reduce costs.
• Manage delivery progress and stakeholder reporting across global teams.
• Build internal accelerators, reusable frameworks, and assets to speed up delivery.
• Act as SME in client workshops translating requirements into engineering solutions.

Skills

Spark

Kafka

Flink

Databricks

AWS Glue/Lambda

Azure Data Factory

GCP Dataflow

Python

SQL

Scala

Java

DevOps

DataOps

Vector databases

Education

Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related fields

Tools

Databricks

AWS Glue/Lambda

Azure Data Factory

GCP Dataflow

Spark

Kafka

Flink

Python

SQL

Scala

Java

DevOps tooling

Job description

Pursue a Career with Impact

At Deloitte China, we are on a mission to nurture and empower our people to become deep subject matter experts. We offer the perfect platform to unleash your full potential and equip you to thrive on challenges, and partner with our clients to solve their most complex problems. A world of opportunities awaits. Start your adventure and journey with us.

About The Business

Deloitte's Technology & Transformation - EAD - AI & Data is a key unit within Deloitte Consulting. We partner with clients to unlock the full value of their data and AI investments through strategic guidance, modern architecture, and full-cycle execution. Our team brings together deep expertise in enterprise architecture, digital transformation, advanced analytics and Generative AI. We deliver end-to-end solutions from strategy to production-grade, scalable, and governed AI solutions.

About The Job

Sustainable success in AI transformation depends on strong, scalable data foundations. As our Data Engineering Lead, you will architect and deliver the robust data platforms that turn complex data into reliable fuel for AI solutions. You will bridge data infrastructure with high-level AI strategy while leading a team of talented engineers to deliver measurable business value.

Work you'll do

• Provide technical leadership in designing and implementing scalable, robust data platforms and pipelines tailored to diverse client needs.
• Lead and mentor a team of Data Engineers, delivering code reviews, technical guidance, and career development.
• Drive engineering excellence, setting standards for CI/CD, data quality frameworks, automated testing, and DataOps practices.
• Ensure delivery excellence through strong data governance, security, and quality controls.
• Diagnose and resolve mission-critical issues, including production failures, data corruption, performance issue, distributed system bottlenecks across cloud environments.
• Proactively optimize solution performance. Such as tuning Spark jobs, Databricks/BigQuery configurations, and Python/SQL code to improve latency and reduce cloud costs.
• Manage global delivery team, communicate between onshore stakeholders and offshore engineering teams.
• Manage delivery progress and stakeholder reporting.
• Building internal accelerators, reusable frameworks, and assets to improve delivery speed across the firm.
• Act as a technical subject matter expert (SME) in client workshops, effectively translating business requirements into practical engineering solutions.

At the Manager level, you will own complex technical solution, deliver high-quality outcomes with minimal supervision, coach junior team members, actively contribute to the engineering practice and expansion of our service offering.

We are looking for someone with

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related fields.
• 5-8+ years of data engineering experience, with at least 2 years in a leadership or senior architectural role.
• Deep experience with Spark (Batch and Structured Streaming), Kafka, or Flink for distributed data processing.
• Strong proficiency in at least one cloud provider (e.g., Databricks, AWS Glue/Lambda, Azure Data Factory, GCP Dataflow).
• Advanced skills in Python and SQL. Knowledge of Scala or Java is a plus.
• Solid experience with DevOps and DataOps tooling and practices.
• Understanding of vector databases (e.g., Pinecone, Milvus) and the data requirements for LLM fine-tuning/RAG architectures is highly preferred.
• Experience building RAG, agents, or multi-modal AI solutions is a strong advantage.
• Good client-facing and communication skills.
• Certified in cloud data solution (Databricks, AWS,Azure or GCP) would be an advantage.
• Fluent in English and Chinese.
• Working proficiency in Mandarin would be an advantage.

Shape your future through impact that matters

For more than 100 years of history, Deloitte witnessed also had the honor to be part of the economic boom in China by providing industry-leading audit & assurance, consulting, risk advisory, financial advisory, tax & business advisory services to nearly 90% of the Fortune Global 500 Chinese companies and thousands of private companies. Deloitte China today carries on our centenary professionalism and strives to become the undisputed leader in professional services in China with strong responsibility and capabilities in digitalization and multidisciplinary services.

Deloitte has been named China's Top Employer since 2006, Universum's Most Attractive Employer in China since 2008, and the Best Workplaces in Greater China since 2019.

All qualified applicants will receive consideration for employment regardless of their background, experience, identity, ability or thinking style, and if you need assistance during the application process for accessibility reasons this is available upon request. The preferred candidate will be subject to background screening by Deloitte China or by their external third-party provider.

Accessibility assistance

If you need assistance or an accommodation during the recruitment process for accessibility reasons, there will be an opportunity for you to let us know what you need once you begin your application.

Why Deloitte China?

• We are the world's largest professional services firm that changes the world, we lead with purpose and shared values.
• We are the market leader with digital and innovative solutions, we create values for client through our multi-disciplinary services.
• We are recognized as Top Employer in China by the Top Employers Institute* for 14th consecutive years, and made the top 3 for the first time this year!
• We are certified as one of the Best Workplaces in Greater China by Great Place to Work in 2019