Senior Principal Architect, Data Engineering

Mandai Wildlife Group is the steward of Mandai Wildlife Reserve, a unique wildlife and nature destination in Singapore that is home to world-renown wildlife parks which connect visitors to the fascinating world of wildlife. The Group is driving an exciting rejuvenation plan at Mandai Wildlife Reserve, adjacent to Singapore’s Central Catchment Nature Reserve, that will integrate five wildlife parks with distinctive nature-based experiences, green public spaces and an eco-friendly resort.

Job Duties and Responsibilities:

We are seeking a Senior Principal Architect for Data Engineering to serve as the senior technical authority for data and analytics engineering at Mandai. With 10 years or more of experience, the ideal candidate will own the enterprise data architecture and set the standards, patterns, and roadmap for how data is extracted, transformed, governed, and surfaced across the organisation. This role combines deep, hands-on engineering expertise with architectural leadership: designing, building, and governing scalable data, analytics, and AI capabilities, mentoring junior engineering teams, and ensuring data is trusted, secure, and ready to help business users make better decisions.

Enterprise Data Architecture & Strategy

• Define and own the enterprise data architecture, reference patterns, and multi-year data engineering roadmap across the Group.

• Set architectural standards and guardrails for scalable data pipelines, ETL and ELT processes, and analytics platforms, ensuring they are robust, observable, and cost-efficient by design.

• Lead build-versus-buy and platform decisions for data orchestration, storage, and visualisation, balancing current needs with long-term scalability.

• Champion modern data architecture patterns, such as data lakehouse, streaming, and event-driven design, where they deliver clear value.

Data Pipeline & Platform Engineering

• Design, build, and govern robust data ingestion and transformation across diverse internal and external sources, ensuring data quality, integrity, and lineage at scale.

• Develop and optimise SQL queries, scripts, and stored procedures, and set best practices for performance, reusability, and maintainability.

• Orchestrate and manage complex data workflows using tools such as Fivetran and dbt.

• Enable self-service analytics and reporting through well-modelled, trusted, and well-documented datasets.

Analytics, AI & Insight Enablement

• Lead the delivery of analytics, data engineering, and AI solutions that help business users make faster, better-quality decisions.

• Partner with analytics and DevSecOps teams to operationalise AI models and algorithms, from prototype through to production.

• Establish visualisation standards across tools such as Microsoft Power BI or Streamlit to ensure consistent, trustworthy reporting.

• Collaborate with cross-functional teams to understand business requirements and translate them into well-architected technical solutions.

Data Governance, Security & Trust

• Establish and enforce data governance, security, and privacy protocols, maintaining compliance with company policy, regulatory requirements, and industry standards.

• Embed data quality, metric definitions, and lineage controls that make data trustworthy and auditable across the organisation.

• Define and uphold standards for documentation of data engineering processes, workflows, and systems.

• Act as a steward of trust, ensuring data practices strengthen Mandai’s reputation and ESG commitments.

Technical Leadership & Capability Building

• Provide technical leadership and mentorship to junior data engineers, raising the organisation’s data engineering maturity.

• Provide senior-level troubleshooting and resolution of complex data issues, ensuring minimal disruption to business operations.

• Define internal data engineering standards, reference patterns, playbooks, and best practices.

• Stay current on industry trends and emerging technologies, advising on practical adoption over experimental novelty.

Job Requirements:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.

• Minimum of 10 years of experience in data engineering, including significant time in lead, principal, or architect roles, with a focus on data extraction, translation, enrichment, and visualisation.

• Proficiency in Fivetran and dbt for data orchestration and pipeline management.

• Proficiency in Streamlit and Microsoft Power BI for data visualisation.

• Experience with programming languages such as Python, Java, JavaScript, and SQL.

• Expertise in SQL and other database management systems.

• Experience in developing and deploying AI models and algorithms.

• Deep understanding of data governance, security, and compliance at enterprise scale.

• Excellent problem-solving skills and attention to detail.

• Strong communication and collaboration abilities, with a track record of mentoring engineers and influencing stakeholders.

• Experience with Snowflake data technologies such as Horizon Catalog, Cortex Code, and Cortex Analyst.