● Leads the delivery of services, ensuring that agreed service levels, security requirements and

other quality standards are met.

● Responsible for day-to-day management, resource planning and work allocation to meet agreed

service levels.

● Monitors the performance of technology services. Provides appropriate status and other

reports to internal and external stakeholders

● Identifies the communications and relationship needs of stakeholder groups. Translates

communications/stakeholder engagement strategies into specific activities and deliverables.

● Leads investigation of all breaches against targets and service KPI and initiates remedial

activities.

● Reviews the effectiveness of operations support processes and practices. Identifies, evaluates

and manages the adoption of appropriate tools, techniques and processes for operations

support.

● Drives innovation and continuous improvement to increase service performance and customer

satisfaction.

● Develops plans for disaster recovery together with supporting processes.

● Ensures that processes and practices are aligned across teams

● Lead engagement with delivery teams to confirm that all services developed (i.e. applications,

platforms, database, etc) meet the service acceptance criteria and are to the required standard

for production.

Requirements:

● Education – At least graduate with a Bachelor’s or Master's Degree in IT, Computer Science,

Engineering, or any related course.

● Related Work Experience – at least 5 years of experience in data engineering, data analytics, or

related fields.

○ Proficiency in Python and Java, with experience in other programming languages as a

plus.

○ Hands-on experience with data manipulation tools (e.g., pandas, dplyr, or Spark).

○ Proficiency in Extract, Transform, and Load (ETL) processes for efficient data pipeline

management.

○ Expertise in both SQL and NoSQL query languages for database interaction and

management.

○ Experience with big data storage and processing solutions, such as MongoDB, Spark,

Hive, Snowflake, Redshift, or similar technologies.

○ Experience with cloud-based or server-based data processing environments (e.g., AWS,

Azure, GCP).