Data Platform Engineering Lead - Trust Bank

Employer
Standard Chartered Bank
Location
Singapore, Singapore
Salary
Competitive
Posted
26 Jun 2022
Closes
11 Jul 2022
Ref
15590609
Job Function
Other
Industry Sector
Finance - General
Employment Type
Full Time
Education
Bachelors
Head of Data Platform Engineering- Digital Bank

We are New! We are Growing! We are a Startup! We are Trust Bank!

We are looking for strong talent to be working within our brand new Digital Bank. We are a growing venture with new and exciting problems to solve on a daily basis focused on working towards the mission of creating Singapore's Digital Bank. We are well-backed, agile and do focused work within interdisciplinary teams. If this sounds like a place where you want to work - don't hold back!

Job Description

Reporting directly to the CTO of Trust Bank, this role will manage a direct and indirect team to affect incremental business outcomes across all key lines of the consumer bank. Specifically, the role holder will be responsible for four primary areas - data platform engineering, AI / ML, data engineering and data visualization.

The role holder will define and execute relevant roadmaps across all four areas, ensuring key stakeholders are engaged and consulted, and roadmaps are aligned to business priorities to drive revenue outcomes. In particular, the role holder will partner closely with Technology to standardize data platforms, simplify architecture, and deliver and run the platform.

Data Platform Engineering
  • Define technology roadmap for data platforms in partnership with Technology, engaging relevant stakeholders to ensure required capabilities are identified and incorporated into future state architecture
  • Drive technical vision, technology stack selection and identification of emerging technologies as it relates to big data and artificial intelligence
  • Build sponsorship for transformation and investment, ensuring a robust business case is presented spanning capabilities, risk, and cost
  • Ensure effective integration with data, models and messaging platforms to achieve agile delivery of new use cases
  • Act as gatekeeper with respect to change on data platforms, ensuring changes are in line with platform vision
  • Partner with Technology to review proposed changes to data platforms to ensure solutions are robust, well designed and in line with platform vision
  • Ensure all risks and issues with respect to data platforms are identified and corrective actions defined and delivered in a timely manner
  • Ensure compliance with policies and standards for all data platforms (including but not limited to information security, entitlements, COB, records management, etc.)
  • Work closely with the Production Support team in the event of an incident, ensuring incidents are addressed in a timely manner and root cause identified and addressed via corrective action plan where appropriate

Artificial Intelligence / Machine Learning
  • Define the roadmap to accelerate the use of AI / ML across the Bank, ensuring the roadmap is aligned to business priorities
  • Act as an evangelist for AI / ML, educating stakeholders as to how AI / ML can drive value for the bank at scale
  • Work closely with key stakeholders to identify ways in which AI / ML can be leveraged to solve business problems
  • Lead a team of Data Scientists based optimize and productionize AI / ML models across the Bank, in line with the defined roadmap
  • Ensure that all AI / ML models are deployed in line with Trust policy, and relevant regulations

Data Engineering
  • Guide the future direction of data strategy and processes, including intake, sources, database design and structure, data integrity and database tools.
  • Working in close partnership with the Business Analytics & Insights team to define the data needs of the business, aligned to strategy and priorities and ensure the logic for data elements is defined and data is available in the data harbour.
  • Partner with Technology to ingest the required data assets and deliver reporting cubes, lead test and deployment of reporting cubes and underlying data layers.
  • Transform data and information into insights that inform high-level strategy and tactical decision-making in support of revenue and profitability objectives.
  • Be a champion for a data driven culture, lead a team of cross-functional engineers and support and train staff in data systems and reporting.
  • Develop and execute a plan to maximize self-service capabilities for internal users and customers.
  • Proactively communicate and collaborate with internal and external customers to ensure information needs are formalized and understood and be conversant in the functional requirements for information exchange.
  • Ensure compliance with Trust policies and standards with respect to data management / data governance.

Data Visualization
  • Develop and execute the data visualization roadmap.
  • Drive adoption of business intelligence and analytics solutions, gaining support of multiple stakeholders and driving adoption.
  • Lead the regional visualization COE which serves as the regional center of data visualization skills, expertise, people, process, and tools / applications.
  • Develop and drive adoption of data visualization standards and principles, ensuring there is consistency across the board.

Knowledge / Experience:
Essential:

  • 5+ years of overall experience in similar roles, within the financial services industry.
  • Expert technical understanding of technology required to implement, execute self-service insights, and campaign delivery
  • Knowledge of statistical modelling including development and model deployment on enterprise platforms
  • Strong understanding of data architecture, data quality and related technologies
  • Experience in Driving Computational Governance - building abstractions in the form of core-libraries, helm charts, automation pipelines to provide strong technical controls and guarantees (Interoperability of data, Observability, Lineage, Security, and encryption standards) in a decentralised context.
  • Skilled in banking data security requirements (container security, access management, encryption, and protection of customer data).
  • Experienced with customer analytics - understanding individual customer behaviour patterns in acquisition, engagement, retention using individual propensity models, segmentation approaches, etc.
  • Experience with enterprise-level budget planning and management processes Uses Confluence, JIRA, and other agile team process tools to accelerate team outcomes
  • Must possess and demonstrate a "commercial mindset"

Skills:
Essential:
  • Stakeholder management - experience working with and managing multiple senior stakeholders
  • Influencing skills - acts as an evangelist for data platforms and capabilities
  • Self-motivated and accountable - demonstrated ability to follow through to execution
  • Project management - ability to lead cross functional teams towards a common vision
  • Organized - can juggle multiple, potentially competing priorities with assurance
  • Detail oriented - obsessed with quality
  • Superior communication - able to clearly articulate complex strategies / techniques and ideas, in both oral and written form, to senior management, with associated confidence
  • Execution oriented - doesn't remain in the theoretical; is able to make choices / decisions in the name of delivering rapid business impact
  • Collaborative - easy to work with, across all levels of the organization; builds effective working relationships
  • Bias for change - actively seeks out ways to improve processes, people, etc.
  • Influencing - able to influence outcomes without necessarily direct authority; experienced navigating large complex organizations to achieve results

Role Specific Technical Skills

  • Knowledge of big data platforms incorporating the data ingestion, query, governance, and deployment life cycle (Kafka, Athena, Python, Spark) on cloud-based deployment standards
  • Experience with modern data engineering tooling in AWS Cloud (AWS Glue, Athena, EMR, Sagemaker, Lambda)
  • Working experience with real time data and reporting such as Kafka Streams, Flink, Spark Streaming.
  • Knowledge of Kubernetes platform management with experience in Airflow, deployment of Confluent Kafka on K8
  • Understanding of distributed systems and providing high availability and durability guarantees for all storage systems within the bank (Kafka, RDS, etc).
  • Data Base Administration skills to manage AWS RDS and Dynamo DB.
  • Experience in designing and implementing Data Mesh architecture

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