Purpose

The Data & AI Engineer in the data & AI team of Keytrade Bank is responsible for building end-to-end AI systems and data pipelines that support both the data & AI team and their end users. These systems allow developing advanced algorithms and automated IT operations workflows to transform raw data into fully automated data & AI products. This role demands application of advanced data processing technologies, methodologies and techniques, including Machine Learning and AIOps methodologies. The mission is to simplify data & AI access for business users and data department members, while aligning with operational objectives for monitoring, troubleshooting and proactive incident resolution. The secondary mission is to industrialize advanced machine learning algorithms by establishing and maintaining an MLOps and AIOps framework, in collaboration with the data & AI squads and IT teams.

Responsibilities

Data & AI Systems Design, Management, and Monitoring (20% time spent):

1. Design, build, maintain and test robust, scalable, and efficient AI systems for collecting, storing, and analysing data at scale.
2. Collaborate with cross-functional teams to implement best practices in data & AI applications design across the organization.
3. Incorporate DevOps, MLOps and AIOps principles for continuous delivery, intelligent alerting and automated system maintenance.
4. Lead the development, maintenance, and improvement of the combined MLOps and AIOps framework in collaboration with data & AI scientists and the IT department.
5. Monitor data & AI systems in production, ensuring high availability, performance, anomaly detection and compliance with SLAs.

Data Acquisition, Transformation, and Democracy (50% time spent):

1. Understand the needs of the data & AI team and final business users in terms of data and data structure.
2. Develop pipelines to provide the necessary data in the required format/structure.
3. Promote data democracy by making the needed data available in a self-serve mode and helping in deploying and maintaining Data Visualization and Reporting solutions.

Automation, Code Management, and Compliance (30% time spent):

1. Identify data & AI related processes that can be automated within the Data & AI team and develop the required CI/CD and AI-driven pipelines for deployment and testing
2. Act as a gatekeeper for code versioning, coding standards and observability best practices across the Data & AI team.
3. Ensure compliance with data and AI operating model, standards, policies, and procedures.

Competencies

• Solid understanding of database technologies (like SQL) and data pipeline orchestration tools (such as Airflow).
• Experience with ETL processes (Extract, Transform, Load), including data transformation tools like dbt or Wherescape
• Strong experience with Linux and shell scripting knowledge a plus
• Proficiency in relevant programming languages such as Python, Scala, or Java
• Data Modeling and Management: Deep understanding of data modeling concepts, and the ability to effectively manage, manipulate and analyze large or complex datasets.
• Extensive with cloud platforms like Azure and FABRIC and their data services
• System Design, DevOps, MLOps & AIOps: knowledge of principles for system management and continuous delivery.
• Machine Learning Knowledge: An understanding of machine learning algorithms and processes, and the ability to work with data scientists to operationalize these models.
• Analytical Thinking: Ability to approach problems in a logical, systematic way, and to break down complex issues into manageable parts.
• Communication Skills: Excellent written and verbal communication skills, and the ability to explain complex data concepts to non-technical stakeholders
• Problem-Solving Skills: The ability to identify, analyze, and devise solutions for complex problems
• Project Management: Ability to plan, organize, and manage resources to bring about the successful completion of specific project goals and objectives.