Director, Data Engineering

ACG_3369_JOB Our client is a leading financial services corporation, who is looking for a qualified candidate to join their firm. 1. Data Architecture & Platform Strategy Lead teams in designing and implementing scalable programs, algorithms, and automated workflows to process, integrate, and evaluate large and complex datasets. Establish and institutionalize best practices for data architecture and infrastructure to support advanced analytics and enterprise data utilization, leveraging modern and emerging technologies. Guide teams in identifying and resolving complex data ingestion and transformation challenges across business domains. Assess and optimize existing data architectures, ensuring alignment with evolving business and analytical requirements. Oversee the delivery of enterprise data products and services into operational systems and business workflows, ensuring compliance with regulatory and governance standards. Review internal and external business requirements related to data operations and recommend enhancements to storage, systems, and processing capabilities to support sustainable growth. 2. Data Integration & Engineering Excellence Define and execute enterprise strategies for acquiring and integrating data from diverse internal and external sources into centralized platforms and advanced analytics environments. Collaborate closely with Data Science teams to translate modeling requirements into reusable, scalable data assets that accelerate machine learning model development and deployment. Architect, build, and maintain high-performance data pipelines and ETL/ELT frameworks to support analytical reporting and real-time decision-making capabilities. Ensure data assets are structured, catalogued, and governed to maintain high standards of quality, reliability, scalability, and performance. Integrate new data sources to enhance throughput and optimize the performance of existing systems, ensuring data completeness across metadata platforms. 3. Project & Operational Leadership Manage large-scale data engineering initiatives, addressing project risks, technical challenges, and evolving business priorities to maintain operational excellence. Partner with cross-functional leaders to remove roadblocks, resolve resource constraints, and drive continuous improvement through structured post-implementation reviews and root cause analyses. Champion enterprise-wide digital transformation initiatives, ensuring strong execution and alignment with strategic objectives. 4. People & Organizational Leadership Lead workforce planning and resource allocation (including headcount and cost management) for the data engineering function. Recruit, onboard, and retain high-caliber engineering talent to build a high-performing organization. Define and communicate functional objectives, KPIs, action plans, and performance expectations across reporting lines. Manage performance evaluation cycles and provide ongoing coaching and feedback. Define capability requirements and support professional development through training, mentoring, and structured growth plans. Recognize and reward contributions aligned with shared organizational goals. Act as a cultural ambassador and role model, reinforcing corporate values within the function. Ensure effective communication of relevant HR programs and policies to team members. Requirements Bachelor’s or Master’s degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering, Information Technology, or related quantitative disciplines. 10–12+ years of experience in Data Engineering, Big Data platforms, or enterprise data infrastructure, including at least 5 years in leadership roles. Demonstrated success in designing, building, and operating large-scale Data Lake or enterprise data platform solutions, ideally within banking or financial services environments. Hands-on experience with cloud platforms (e.g., AWS) and modern big data frameworks such as Databricks and Apache Spark. Strong expertise in dimensional data modeling, ETL development, data warehousing methodologies, and optimization of large-scale data pipelines. Proven architectural experience or close collaboration with enterprise architects on complex data ecosystems. Deep experience monitoring distributed systems and applying structured, algorithmic approaches to diagnosing and resolving data and infrastructure issues. Strong understanding of information security principles and compliant data management practices. Extensive experience leading Agile teams in enterprise-wide digital transformation initiatives, with mastery of Agile principles, Scrum methodologies, and change management practices. Recognized expertise in data and analytics technologies, with strong awareness of industry trends and emerging capabilities. Demonstrated history of architecting, developing, and deploying high-performance microservices and/or large-scale recommendation systems serving millions of users. English proficiency aligned with internal organizational standards. Contact: Huong Do Due to the immense number of applications, only shortlisted candidates will be contacted.