Data Engineer (DST)

Borr Drilling; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

A leading company seeks an experienced Data Engineer to design, develop, and maintain robust data pipelines in a cloud environment to support healthcare analytics. The ideal candidate will have significant experience in data management and architecture, capable of leading initiatives and mentoring junior engineers. This role offers an opportunity to engage in meaningful projects that enhance health system transformation.

Qualifications

• 8+ years of experience in data engineering.
• Strong background in building and managing data architectures.
• Proficiency with cloud data platforms and data pipeline tools.

Responsibilities

• Lead the design and development of data pipelines for healthcare analytics.
• Collaborate with teams for data engineering solutions.
• Document data workflows and ensure data quality.

Skills

Data Pipeline Management

SQL

Python

Communication Skills

Education

Bachelor’s Degree in Computer Science

Tools

Apache Airflow

Kafka

Spark

AWS

Snowflake

Redshift

BigQuery

Job description

MOHT envisions a transformed health system that is patient-centric, data-driven and digitally-enabled to better empower health, prevent disease and provide excellent value-based care. To realise this vision, MOHT’s mission is to design and implement innovative solutions essential for the desired health system transformation.

Technology plays a significant role in MOHT’s projects and experiments, and in its operating environment. MOHT adopts an agile approach using rapid and continuous build-measure-learn cycles that identify, develop, deliver and adapt technology to improve health. They work closely with IHiS and implementation partners. This allows MOHT’s teams to be responsive to real needs, as demonstrated by actual data, and nimble in evolving prototypes and scalable solutions.

The main tools being used are:

• Agile development on cloud based environment

• Digital solution architecture design, development and operation

• Data analytics and modelling to understand healthcare flows and resource usage

Artificial Intelligence

Current Initiatives:

• Digital application for mental wellness
• Passive and active sensing tools for patient lifestyle understanding and improvement
• Tele-health monitoring solutions for connected care
• Mobile patient and clinical applications
• Digital phenotyping
Data analytics, including for patient flow analysis

JOB RESPONSIBILITIES

• Lead the design, development, and maintenance of scalable and secure data pipelines and architectures to support healthcare analytics and digital health solutions.
• Collaborate with cross-functional teams to understand data needs and translate them into robust data engineering solutions.
• Manage and optimize data ingestion, transformation, and storage processes across structured and unstructured data sources.
• Ensure data quality, integrity, and governance across all data platforms.
• Drive the adoption of best practices in data engineering, including CI/CD, testing, and monitoring.
• Mentor and guide junior data engineers and contribute to team capability building.
• Work closely with data scientists, analysts, and application developers to enable data-driven decision-making.
Document data workflows, architecture, and operational procedures for knowledge sharing and continuity

JOB REQUIREMENTS

Required:

• Bachelor’s degree (or above) in Computer Science, Data Engineering, Information Systems, or a related field.
• At least 8 years of experience in data engineering, with a strong background in building and managing data pipelines and architectures.

Must have:

• Hands-on experience with cloud-based data platforms (AWS preferred or Azure, or GCP).
• Proficiency in data pipeline tools (e.g. Apache Airflow, Kafka, Spark).
• Strong SQL skills and experience with relational and NoSQL databases.
• Strong Python programming skills
• Experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
• Familiarity with data governance, security, and compliance in healthcare or regulated environments.
• Plus: Experience with healthcare data standards (e.g., FHIR, HL7) and DevOps practices.
• Leadership: Ability to lead data engineering initiatives, coordinate with stakeholders, and manage project timelines and deliverables.
• Good communication skills, both written and verbal.