Data Engineer Lead 54K

Michael Page International (HK) Ltd; Hong Kong; On-site; HKD 542,000 - 603,000; Full time

Benefits offered by this job

Medical

Gratuity (10%)

Job summary

Michael Page International (HK) Ltd seeks a senior data engineering leader to drive a team responsible for a cloud-based data platform supporting analytics and ML workloads.

You will guide Spark on AWS EMR, real-time data ingestion pipelines, and end-to-end data governance, while coaching engineers and collaborating with data science teams to deliver scalable solutions.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or related technical discipline, or equivalent industry experience.
• At least 6 years of experience in data engineering, including leadership and mentoring experience.
• Strong technical leadership with ability to establish standards, mentor engineers, and review designs and code.
• Ability to communicate and present technical solutions to technical and non-technical audiences.
• Proven hands-on expertise with Apache Spark on AWS EMR, including pipeline architecture, performance optimisation, and cost management.
• Experience designing and supporting streaming API services for real-time data ingestion, consumption, and API-driven delivery.
• Solid experience across AWS data services including S3, Glue, Lake Formation, Athena, Redshift, Step Functions, and Lambda.
• Proficiency in Python, with additional expertise in React and Node.js within a Backend-for-Frontend architecture.
• Ability to contribute solution concepts within defined architecture standards and governance frameworks.
• Understanding of MLOps principles and supporting self-service capabilities for data science teams.
• Experience with streaming and messaging technologies such as Kafka or Spark Streaming, plus strong SQL and data modelling skills.
• Interest in AI/generative AI is advantageous but not required.
• Excellent communication, stakeholder engagement, and coaching abilities.
• Fluent Cantonese and English required; Mandarin is an advantage.
• Experience in consulting, professional services, or technology services environment preferred.

Responsibilities

• Lead and develop a team of data engineers, providing coaching to strengthen technical capability and delivery excellence.
• Offer hands-on technical direction by defining engineering best practices, reviewing solution designs and code, and promoting high-quality outcomes.
• Propose and detail solution designs that align with architecture standards, governance requirements, and delivery frameworks.
• Communicate technical approaches effectively to stakeholders and project teams, explaining key design choices and trade-offs.
• Guide Spark workloads on AWS EMR for batch and real-time data processing.
• Oversee design and management of streaming API solutions supporting real-time ingestion, consumption, and delivery.
• Support self-service data access for data science users through curated data assets and governed delivery mechanisms.
• Advocate strong MLOps practices, including model deployment, monitoring, and lifecycle support within the platform environment.
• Contribute to lightweight user-facing and service-layer components using React and Node.js within a Backend-for-Frontend architecture.
• Collaborate with stakeholders, data science teams, and platform specialists to translate requirements into scalable, secure, cost-efficient solutions.
• Drive data governance best practices across data quality, lineage, integrity, and security.
• Participate in emerging AI and generative AI initiatives with technical input.

Skills

Leadership

Spark on AWS EMR

Python

React

Node.js

Data governance

MLOps

Stakeholder engagement

Coaching

Communication

Education

Bachelor's degree in Computer Science / Engineering / Data Science

Tools

AWS EMR

S3

Glue

Lake Formation

Athena

Redshift

Step Functions

Lambda

Kafka

Job description

$48600 - $54k p.m. + 10% gratuity + Medical

This role leads a team of data engineers supporting a cloud-based data platform that enables large-scale analytics and machine learning workloads. Success requires strong leadership, deep expertise in Spark on AWS EMR, and the ability to design scalable, governed data solutions.

Our client is a technology-focused organisation operating a modern cloud data environment. The team works closely with business and technical stakeholders to deliver data, analytics, and machine learning capabilities through scalable engineering solutions.

Description

• Lead and develop a team of data engineers, providing coaching to strengthen technical capability and delivery excellence.
• Offer hands-on technical direction by defining engineering best practices, reviewing solution designs and code, and promoting high-quality outcomes.
• Propose and detail solution designs that align with established architecture standards, governance requirements, and delivery frameworks.
• Communicate technical approaches effectively to stakeholders and project teams, explaining key design choices and associated trade-offs.
• Guide the development and optimisation of Apache Spark workloads on AWS EMR for both batch and real-time data processing.
• Oversee the design and management of streaming API solutions supporting real-time ingestion, consumption, and data delivery.
• Support self-service data access for data science users through curated data assets and governed delivery mechanisms, recommending suitable implementation approaches.
• Advocate strong MLOps practices, including model deployment, monitoring, and lifecycle support within the platform environment.
• Contribute to the delivery of lightweight user-facing and service-layer components using React and Node.js within a Backend-for-Frontend architecture.
• Collaborate with stakeholders, data science teams, and platform specialists to convert business requirements into scalable, secure, and cost-efficient solutions.
• Drive best practices in data governance, covering data quality, lineage, integrity, and security throughout the data lifecycle.
• Participate in emerging AI and generative AI-related initiatives, contributing ideas and technical input where appropriate.

Profile

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical discipline, or equivalent industry experience.
• At least 6 years of experience in data engineering, including demonstrated experience leading and mentoring engineering teams.
• Strong technical leadership capabilities with experience establishing standards, mentoring engineers, and reviewing designs and code.
• Ability to communicate and present technical solutions effectively to both technical and non-technical audiences.
• Proven hands‑on expertise with Apache Spark running on AWS EMR, including pipeline architecture, performance optimisation, and cost management.
• Experience designing and supporting streaming API services for real‑time data ingestion, consumption, and API‑driven delivery.
• Solid experience across AWS data services including S3, Glue, Lake Formation, Athena, Redshift, Step Functions, and Lambda.
• Proficiency in Python, with additional expertise in technologies such as React and Node.js within a Backend-for-Frontend architecture preferred.
• Ability to contribute solution concepts and detailed designs within defined architecture standards, delivery patterns, and governance frameworks.
• Understanding of MLOps principles and experience supporting self‑service capabilities for data science teams.
• Experience with streaming and messaging technologies such as Kafka or Spark Streaming, along with strong SQL and data modelling skills.
• Interest in or exposure to AI and generative AI technologies is advantageous but not a primary requirement.
• Excellent communication, stakeholder engagement, and coaching abilities.
• Fluent Cantonese and English language skills are required; Mandarin is an advantage.
• Previous experience within a consulting, professional services, or technology services environment is preferred.

Job Offer

• Competitive monthly salary.
• Usual contractor benefits offered by the organization.