Manager/Senior Manager, Data Engineer

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. You will be working in a dynamic and fast-paced environment, and enjoy navigating challenges and ambiguities to accomplish goals, with opportunities for publication and invention.

mindline.sg is an anonymous digital mental health and wellness platform developed by MOHT. Individuals who use the platform are directed to appropriate channels of mental health support, self-help tools, and self-care exercises based on their profile, needs and preference for help-seeking. The digital first-stop touchpoint consists of a wide array of resources including wellness education, a clinically validated self-assessment for depression and anxiety which triages individuals based on the severity of their mental health needs, a service wayfinding tool that recommends best matched community mental health services based on a help seeker’s profile and location, and interactive resources including an AI therapy chatbot. Individuals are also able to chat with counsellors in real time through a text widget.

In addition to the suite of content and self-help tools made available, individuals can join let’s talk, our mindline community forum. This moderated safe space allows young people to express their feelings, thoughts and questions without fear of judgement, and receive advice and support from mental health professionals, peer supporters and like-minded youth. In the mindline.sg team, we are continuously exploring, improving and expanding our suite of tech solutions to better meet the needs of the population. Our goal with is to build a world-class digital mental health ecosystem that destigmatises, promotes help-seeking, and supports clinicians and professionals in the delivery of efficient and timely care.

Overview

Summary of the Role

We are seeking a Data Engineer who will lead the development, optimisation, and maintenance of mindline.sg’s data infrastructure. This individual will work closely with the Data Analyst, product teams, and researchers to ensure data flows are efficient, accurate, and secure—enabling high-quality analytics and research.

This role is ideal for someone who enjoys building robust pipelines, implementing modern data engineering practices, and contributing to digital health solutions with real-world public health impact. You will be responsible for building scalable data systems that underpin everything from real-time dashboards to published research.

Job Responsibilities

• Build and maintain scalable ETL/ELT pipelines using a combination of Python, shell scripts, and SQL to ingest data from various sources such as CSV files, Spreadsheet files, APIs.
• Configure and orchestrate ETL workflows; ensure timely data ingestion and transformation.
• Design and maintain data schemas and contribute to database engineering with a strong focus on scalability, data integrity, and governance.
• Collaborate with frontend developers to ensure data pipelines align with interface requirements, while upholding data access controls and governance standards.
• Clean, structure, and transform data into analytics-ready formats using SQL and Python for temporal and historical analysis.
• Create interactive dashboards and charts with Metabase, Superset, or similar dashboarding tools to track metrics and data pipeline progress.
• Develop micro-APIs for internal use cases and data integration.
• Monitor data quality through alerts and generate real-time reports to flag inconsistencies or anomalies.
• Optimise SQL queries and visualisation layers for performance and maintainability.
• Support CI/CD, DevOps, MLOps, and automation workflows.
• Integrate modern ML tools and models, including LLMs, where applicable.
• Collaborate with cross-functional teams to deliver ad-hoc analytics report, perform data tasks, and ensuring compliance with all data and privacy requirements.

Job Requirements

• Proven experience in data engineering, data platform operations, or backend systems.
• Proficiency in Python, SQL, and packages such as numpy and pandas.
• Hands-on experience with CI/CD data pipelines (gitlab/github/Jenkins) and orchestration tools (e.g., Prefect, Airflow, dbt).
• Experience with cloud infrastructure (AWS) and database tech (e.g. MySQL, postgreSQL).
• Experience in basic DevOps such as Docker, Kubernetes.
• Familiarity with ML Ops (e.g. KubeFlow, MLFlow) platforms preferred.
• Experience with deep learning tools preferred.
• Experience or familiarity with LLM workflows: prompt engineering, fine-tuning, model distillation.
• Strong collaboration skills and ability to communicate effectively with analysts, engineers, product leads, and non-technical stakeholders.
• Ability to work in a fast-paced, collaborative environment and translate operational needs into scalable technical solutions.

Education Requirement(s):

• A degree / postgraduate qualification in Computer Science, Engineering, Information Systems, or a related technical discipline.

Years of Experience Required:

• At least 5+ years of experience in data engineering, ideally in digital product, health tech, or applied research environments.

Seniority level

• Mid-Senior level

Employment type

• Contract

Job function

• Public Health, Hospitals and Health Care, and Health and Human Services

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