Senior Manager, Data Platform

Senior Manager, Data Platform

Kuala Lumpur, Malaysia

Responsibilities:

Data Platform Strategy & Leadership

• Provide strategic leadership and direction for the trading data and analyticsplatform
• Define and execute the data platform roadmap aligned with trading businessobjectives and technology strategy
• Own the vision and architecture for real-time and batch data ingestion,processing, and analytics
• Drive innovation in data platform capabilities including advanced analytics,machine learning, and real-time insights
• Partner with Head of Trading Digital to align data initiatives with broader digitaltransformation goals
• Establish and communicate data platform strategy to senior stakeholders andtrading business units

Unified Trading Data Platform (UTDP) Databricks including other components of PlatformManagement & Optimization

• Own end-to-end responsibility for the UTDP platform architecture, performance, and reliability
• Design and optimize data pipelines for ingesting 30+ external market data feeds (Bloomberg, Reuters, ICE, exchanges, etc.)
• Manage integration of 12+ internal data sources (trading systems, risk platforms, positions, P&L, reference data)
• Ensure low-latency data processing and delivery to meet trading requirements (sub-second to real-time)
• Implement Delta Lake architecture for reliable, versioned, and ACID-compliant data storage
• Optimize cluster configurations, auto-scaling, and cost efficiency across compute and storage
• Establish monitoring, alerting, and observability frameworks for platform health and performance

Data Ingestion & Integration

• Design and implement robust data ingestion frameworks for diverse data sources and formats
• Build scalable ETL/ELT pipelines using Apache Spark, Delta Live Tables, and Databricks workflows
• Manage real-time streaming data pipelines for tick data, order book updates, and market events
• Ensure data quality, validation, and reconciliation across all ingestion processes
• Implement change data capture (CDC) mechanisms for internal system integrations
• Coordinate with market data vendors and internal system owners on data delivery specifications
• Establish data lineage tracking and metadata management across the platform

Analytics & Data Services Delivery

• Deliver high-performance analytics services to trading tools, risk systems, and business intelligence platforms
• Build and optimize SQL analytics endpoints for interactive querying and reporting
• Develop APIs and data services for downstream consumption by trading applications
• Enable self-service analytics capabilities for traders, quants, and business users
• Implement caching strategies and query optimization for low-latency data access
• Support advanced analytics use cases including back-testing, scenario analysis, and attribution analytics
• Integrate machine learning workflows for predictive analytics and trading insights

Dashboard & Reporting Development

• Own and manage the development of internal dashboards and reporting solutions using Power BI and other organizational reporting tools
• Lead the design and implementation of interactive dashboards for trading, risk, operations, and executive management
• Establish dashboard design standards, best practices, and governance frameworks
• Build Power BI solutions including data models, semantic layers, and complex DAX calculations
• Integrate Power BI with Databricks and other data sources for real-time and near-real-time reporting
• Manage Power BI workspace administration, security, and row-level access controls
• Develop automated report generation and distribution processes
• Evaluate and implement additional reporting tools (Tableau, Qlik, custom web-based solutions) as needed
• Partner with business users to gather requirements and translate into effective visualizations
• Ensure dashboard performance optimization and user experience excellence
• Provide training and support to enable self-service dashboard creation by power users

Data Governance & Quality Management

• Establish and enforce data governance policies, standards, and best practices
• Implement comprehensive data quality frameworks with automated validation and reconciliation
• Define data ownership, stewardship, and accountability across the organization
• Ensure data security, access controls, and compliance with regulatory requirements
• Build data cataloging and discovery capabilities using Unity Catalog or similar tools
• Establish data retention policies and lifecycle management procedures
• Monitor data quality metrics and drive continuous improvement initiatives

Performance & Reliability Engineering

• Own platform SLAs for data availability, latency, and accuracy
• Implement performance monitoring and optimization strategies across all data pipelines
• Design fault-tolerant architectures with high availability and disaster recovery capabilities
• Conduct performance tuning for Spark jobs, queries, and data processing workflows
• Establish capacity planning processes to support growing data volumes and user demands
• Lead incident response for platform issues and conduct root cause analysis
• Implement automated testing, deployment pipelines, and CI/CD practices

Technology Innovation & Modernization

• Drive continuous technology innovation leveraging latest Databricks features and capabilities
• Evaluate and implement emerging technologies in data engineering, streaming, and analytics
• Lead proof-of-concepts and pilots for new data platform capabilities
• Modernize legacy data infrastructure and migrate workloads to cloud-native architectures
• Integrate AI/ML capabilities including Databricks ML Runtime and MLflow
• Stay current with industry trends and best practices in data platforms and analytics
• Champion automation, infrastructure-as-code, and DevOps practices

Team Leadership & Development

• Lead, mentor, and develop a high-performing team of data engineers, analytics specialists, and BI developers
• Recruit top technical talent with expertise in Databricks, Spark, Python, Power BI, and data engineering
• Establish clear roles, responsibilities, and career progression paths for team members
• Foster a culture of innovation, collaboration, and continuous learning
• Provide technical coaching and develop expertise in modern data technologies
• Conduct performance reviews, set objectives, and manage talent development
• Build strong partnerships with offshore/nearshore engineering teams if applicable

Stakeholder Management & Collaboration

• Partner with Front Office trading desks to understand data and analytics requirements
• Collaborate with Quantitative Research teams on analytical models and data science initiatives
• Work closely with Risk, Finance, and Operations on data integration and reporting needs
• Coordinate with Enterprise Architecture, Cloud Infrastructure, and Security teams
• Manage relationships with market data vendors and external data provider
• Present data platform strategy and progress to senior management and steering committees
• Gather feedback from business users and continuously improve data services

Budget & Vendor Management

• Manage platform budget including cloud infrastructure costs, vendor licenses, and team resources
• Optimize cloud spend through efficient resource utilization and cost governance
• Negotiate contracts with Databricks, market data vendors, and technology suppliers
• Evaluate build vs. buy decisions for data platform components
• Track ROI and business value delivered by data platform investments
• Forecast future infrastructure needs and budget requirements

Requirements:

• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or related technical field; Master's degree preferred
• 17-20 years of progressive experience in data engineering, data platforms, or analytics
• Minimum 8-10 years in leadership roles managing technical teams
• Minimum 5+ years hands-on experience with Databricks platform
• Deep experience in financial services, trading, or capital markets environments
• Proven track record designing and implementing large-scale data platforms processing terabytes of data
• Experience with real-time/low-latency data systems for trading or high-frequency applications
• Experienced in Data strategy & governance, Advanced analytics & data architecture, Leadership of data teams
• Experienced in AI/ML strategy, Data monetization & business value realization, Financial/trading analytics
• Experienced in Data Analyst, Data Engineer, IT/Software/Data Architecture.