Purpose of the Role:
The Associate Director, Data Engineering is responsible for the design and implementation of business intelligence, analytics and big data solutions for the Bank. The incumbent leads the data engineering team in the design, build out and management of the Bank’s data infrastructure, ensuring it is reliable and utilizes a high degree of automation around the set-up and maintenance and includes the introduction and incorporation of artificial intelligence (AI) / machine learning, and provides high-value, timely analytics and data solutions. The incumbent owns & drives the Bank’s data engineering roadmap, data analytics initiatives, building of new systems where required and provides support on technology strategy and direction.
Key Accountabilities:
- Leads, develops & maintains mapping the design, development and implementation of the data engineering practice and roadmap, including AI / machine learning concepts to ensure achievement of the strategic goals around automation to aid in the ability to make sound decisions across the Bank.
- Defines & determines the scope of different business technology related initiatives in collaboration with stakeholders to ensure the solutions implemented are fit for purpose.
- Drives & leads new capabilities in data engineering and data integration across the enterprise to ensure the Bank’s data environment is always current and adapting to the various changes in requirements based on business needs and new data developments.
- Builds, leads & manages the required infrastructure and site reliable engineering (SRE) to enable optimal extraction, transformation and loading of data from a variety of data sources along with an efficient, stable and sustainable operation.
- Defines & leads the development of new data solutions and accelerators to enable the team to deploy the data platform and engineering services at scale, and thus providing efficient and effective data solutions.
- Provides thought leadership for all data solutions, including verifying requirements, defining architecture, developing implementation plans, and providing designing data solutions that meet and exceed customer expectations.
Critical Knowledge & Skills Required:
- At least 12 years of experience in big data and / or data warehouse, including at least 8 years of experience in leading data engineering and operations
- Experience in managing large scale data warehouse / data lake in both on-prem and cloud with high availability and scalability
- Experience with Python and Pyspark is crucial, as well as working with full data-science pipelines from prototyping to deployment.
- Experience in data management, data architecture and design
- Strong technical knowledge of data integrations including a data engineering framework
- Experience with DevOps tools and environment
- Experience with cloud environment – AWS, Azure, GCP
- Experience with monitoring and load balancing tools
- Proven & strong project-management experience,
- Experience with agile / scrum
- Knowledge of and experience with data-science technology
- Proven & current knowledge of and experience with statistics and / or machine learning
Experience Required:
- Master’s degree with a focus on math / statistics / econometrics / computer science (preferably with specific attention for machine learning and / or artificial intelligence).
JOB SNAPSHOT:
Category: Technology
Function: Technology
Position reports to: Director, Data & Innovation, TI&I
