Major Accountabilities (Describe the 5-7 main results of this role to be achieved)

• Assist the Data & Analytics team with technical issues and support data infrastructure needs, including those related to machine learning pipelines and dashboard development.
• Collaborate with Business Analysts and other stakeholders to translate business requirements into technical specifications and actionable insights.
• Work closely with Data Scientists to streamline data workflows and support the development, deployment, and monitoring of machine learning models.
• Design, build, test, and maintain optimal data platform architecture in either AWS or Snowflake with DD&IT (i.e., IT Dept.).
• Leverage Snowflake’s advanced capabilities to manage and optimize large-scale data warehousing and analytics.
• Build infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources in partnership with DD&IT.
• Apply best practices in data quality, data security, and data governance.
• Develop and maintain Power BI dashboards and reports to visualize key metrics and support business decision-making.
• Support MLOps practices by integrating model versioning, automated retraining, and performance monitoring into the data platform.

Key Performance Indicators (Indicate how performance for this role will be measured)

• Customer satisfaction evaluation.
• Customer satisfaction rating / feedback by internal stakeholders (Business Franchise Head, relevant management members, and DD&IT members).
• Analytics and machine learning projects resulting in better decision-making or tangible actions.
• Improvement in data literacy and promotion of a culture of fact- and data-driven decision-making.
• Successful deployment and operational stability of machine learning models and Power BI dashboards.

Job Dimensions (Indicate key facts and figures)

Number of associates:

N.A.

Financial responsibility:

(Budget, Cost, Sales, etc.)

N.A.

Impact on the organisation:                              

N.A.

Background (State the required education, experience level, and competency profile)

Education:

• Bachelor’s degree and above in Analytics, Information Systems Management, Computer Science or related fields

Experience/Professional requirement:          

• Experience designing efficient, robust, and automated data pipelines and ETL workflows, and developing cloud-based solutions using AWS, Snowflake, or other cloud providers.
• Hands-on experience with Snowflake, especially in managing large-scale data warehousing and analytics.
• Strong programming skills in at least one object-oriented or functional language such as Python, Scala, or R.
• Familiarity with relational and NoSQL databases, and strong SQL skills.
• Experience with big data tools such as Hadoop, Spark, Kafka, etc.
• Experience in supporting machine learning workflows, including data preparation, feature engineering, model deployment, and monitoring.
• Understanding of MLOps tools and practices (e.g., MLflow, SageMaker, Airflow).
• Proficiency in developing interactive dashboards and reports using Power BI, including DAX, Power Query, and data modeling.
• Proven ability to perform root cause analysis on data and processes to answer specific business questions and identify opportunities for improvement.
• Domain experience in areas such as the pharmaceutical industry, customer analytics, CRM, and digital marketing is a plus.
• Excellent documentation, communication, and presentation skills, including the ability to explain technical findings to non-expert audiences.
• Strong stakeholder management and team collaboration skills.
• Demonstrated leadership in managing cross-functional teams and delivering complex projects.
• Proven ability to foster a collaborative and motivated team environment and to lead through organizational change.

English Skill:

• Business level is required