Service Engagement Assistant Manager, Data Analytics

About ST Engineering

ST Engineering is a global technology, defence, and engineering group with offices across Asia, Europe, the Middle East, and the U.S., serving customers in more than 100 countries. The Group uses technology and innovation to solve real-world problems and improve lives through its diverse portfolio of businesses across the aerospace, smart city, defence, and public security segments. Headquartered in Singapore, ST Engineering ranks among the largest companies listed on the Singapore Exchange.

Our history spans more than 50 years, and our strategy is underpinned by our core values – Integrity, Value Creation, Courage, Commitment and Compassion. These 5 core values guide every aspect of our business and are embedded in our ST Engineering culture – from the people we hire, to working with each other, to our partners and customers.

About our Line of Business - Training & Simulation Systems

Our Training & Simulation Systems business has close to 40 years of experience in delivering innovative learning, training, and simulation solutions to customers in the defence, public safety and security, and enterprise domains. We envision to create a better future together through learning, training, and simulation.

Together, We Can Make A Significant Impact

The Service Engagement Manager, Data Analytics will be a key member of the Learning Insights and Data Analytics Division. He/she will lead the presales and delivery of our data analytics solutions and drive the expansion of our client partnerships. This is a dual-focused role where he/she will be the trusted advisor and project leader for our clients, while also acting as a key driver of business growth within those accounts.

In addition, the role will provide solution architecture leadership across data platforms, cloud and infrastructure environments, ensuring proposed and delivered solutions are scalable, secure, cost-effective, and aligned with enterprise architecture and security requirements.

He/she will manage the entire client lifecycle, from securing initial project commitments to ensuring flawless execution and identifying new opportunities for partnership. The ideal candidate will possess a unique blend of project management expertise, a deep understanding of data analytics, and a talent for building and growing business relationships.

Be Part of Our Success

Strategic Account Management & Business Development:

• Serve as the primary strategic advisor to key client stakeholders, understanding their evolving business challenges and identifying opportunities where our data solutions can provide value.

• Proactively identify and qualify new business opportunities within existing client accounts, expanding our footprint and increasing client lifetime value.

• Develop and present compelling proposals, statements of work (SOWs), and project roadmaps to secure new engagements.

• Collaborate with the pre-sales and business development teams to strategize on account growth and client expansion.

• Manage commercial aspects of the client relationship, including contract negotiations, renewals, and profitability of all engagements.

Project & Service Delivery Leadership:

• Lead the end-to-end delivery of data analytics projects, ensuring they are executed on time, within scope, and on budget.

• Act as the central liaison between the client and our internal delivery teams (data scientists, engineers, BI developers).

• Oversee project governance, including resource allocation, risk management, and quality control.

• Provide regular, transparent communication to both clients and internal leadership on project status and key metrics.

• Coach, develop and supervise team members.

Solution Architecture & Technical Governance:

• Lead the definition and validation of end-to-end solution architectures for data pipelines, data warehouses, data lakes, data lakehouses, and reporting and analytics platforms.

• Translate business and service requirements into target-state architectures, transition roadmaps, technical specifications, and implementation options across cloud, hybrid, and on-premises environments.

• Provide architectural oversight across data, application, infrastructure, integration, security, and operational layers, ensuring alignment with enterprise standards and long-term technology roadmaps.

• Lead architecture reviews and technical assurance activities, identify design risks early, and coordinate mitigation actions with clients, delivery teams, partners, and vendors.

• Guide technology selection and solution trade-offs covering scalability, performance, reliability, security, maintainability, and cost efficiency.

• Ensure solution designs address data governance, metadata, lineage, data quality, auditability, privacy, and regulatory or government security requirements where applicable.

• Oversee integration patterns for structured, semi-structured, and unstructured data, including batch, streaming, API-based, and event-driven approaches.

• Provide technical leadership for cloud-native services, containerisation, orchestration, CI/CD, infrastructure-as-code, observability, and platform modernisation where required.

Data Management Lifecycle and Analytics Expertise:

• Possess a strong understanding of the data Management lifecycle and analytics landscape, including technologies, methodologies, and market trends.

• Translate complex business needs into technical requirements, and articulate the value of our solutions in a clear, compelling manner.

• Act as an internal resource, providing guidance to delivery teams on client-specific business context and priorities.

Qualities We Value

Qualifications and Experience

• Professional Experience: A minimum of 7 years of experience in a client-facing role, including significant experience in both project delivery and business development.

• Data Management Expertise: At least 7 years of experience in Enterprise Data Management. This includes a deep understanding of the data management lifecycle and data analytics services such as Business Intelligence, data warehousing, and machine learning.

• Implementation Experience: Managed at least 3 to 5 end-to-end implementations of data warehouses, data lakes, or data visualization projects.

• Architecture Experience: Demonstrated experience leading solution architecture or technical design for large-scale, enterprise-grade data and analytics solutions, including cloud, hybrid, or on-premises deployments.

• Architecture Deliverables: Proven ability to develop and govern conceptual, logical, physical, target-state, and transition architectures, and to communicate architecture decisions to senior business and technical stakeholders.

Technical Skills

• Data Technologies: Proficient with at least one of the following technologies: Informatica, SSIS, SQL, SQL Server, Azure Data Factory, Data Warehouse, or ETL Framework.

• Visualization & BI Tools: Excellent knowledge of Power BI, Qlik Sense, MicroStrategy, SAS, and Tableau.

• Cloud & Big Data (Preferred): Knowledge of AWS/Azure/Google Cloud services, Hadoop Ecosystem, Data APIs, Unstructured Data, and Data Modelling is a plus.

• Solution Architecture: Strong knowledge of data warehousing, data lakes, data lakehouses, ETL/ELT, data modelling, integration, analytics, and reporting architecture.

• Enterprise Infrastructure & Cloud: Strong understanding of compute, storage, networking, security, public cloud, private cloud, hybrid, and on-premises architecture. Experience with GCC or MCC environments is an advantage where relevant to the engagement.

• Governance, Security & Compliance: Knowledge of data governance, metadata management, data lineage, data quality, encryption, key and secrets management, secure access patterns, auditability, privacy, and compliance controls.

• Modern Platform Engineering: Familiarity with containerisation and orchestration, CI/CD, infrastructure-as-code, APIs, streaming and event-driven integration, observability, performance tuning, workload isolation, and cost optimisation.

• Technical Proficiency: Working knowledge of SQL and Python, with the ability to review solution designs and guide engineering teams. Knowledge of machine learning and MLOps integration is an advantage.

Professional & Interpersonal Skills

• Communication & Leadership: Exceptional communication, negotiation, and presentation skills. Proven ability to lead multiple teams, manage complex relationships, and navigate difficult conversations.

• Architectural Leadership: Ability to lead architecture workshops, design reviews, data governance, and technical assurance discussions, while translating complex architectures into clear business outcomes and delivery decisions.

• Problem-Solving: Strong problem-solving, quantitative, and analytical abilities.

• Project Management: Experience with project management methodologies (e.g., Agile) and tools (e.g., Jira, Salesforce).

• Stakeholder Management: Excellent stakeholder management and influencing skills, covering colleagues, partners, and vendors.

• Mindset: A client-centric, outcome-driven, and quality-focused team player. Must be a self-starter with a proactive, entrepreneurial mindset, capable of working independently to achieve strategic objectives.

• Resilience: Demonstrated ability to effectively work under pressure, especially during high-demand project lifecycles.
  

Our Commitment That Goes Beyond the Norm

• An environment where you will work on cutting-edge technologies and innovative solution architectures.

• A safe and inclusive workplace where diverse perspectives are valued and celebrated.

• Meaningful projects that make a difference in public safety, national security, workforce development, and education.

• A passionate, collaborative, and high-performing culture.

• Competitive remuneration and comprehensive benefits.