M/SM - Data Engineering & AI - 90k

Job Responsibilities

• Supported delivery of data analytics and data platform initiatives from requirements gathering to implementation and deployment.
• Collaborated with business stakeholders, data engineers, and architects to analyse requirements and deliver data-driven solutions.
• Managed project activities, including tracking progress, risks, issues, dependencies, testing, and release coordination.
• Assisted in implementing data governance capabilities, including data quality, metadata management, data lineage, and access controls.
• Worked with cross-functional teams to support data platform enhancements, data integration, and analytics use cases.
• Coordinated with internal teams and external vendors to ensure successful project delivery.
• Supported cloud-based data platforms and analytics technologies across enterprise environments.
• Participated in Agile and SDLC processes, including business analysis, UAT, documentation, and stakeholder engagement.
• Contributed to dashboard and reporting initiatives using data visualisation tools to support business decision-making.
• Promoted data governance best practices and continuous improvement across data and analytics platforms.

Job Requirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 4+ years of experience in data engineering, data analytics, data management, technology delivery, or related fields.
• Good understanding of SDLC methodologies and Agile delivery frameworks.
• Knowledge of data engineering concepts, data modelling, ETL/ELT processes, data visualisation, and analytics.
• Familiarity with enterprise data platforms, data architecture, and modern data management technologies.
• Experience working with analytics platforms such as Databricks, JupyterHub, or similar tools.
• Understanding of cloud technologies including Azure, AWS, Alibaba Cloud, or Huawei Cloud.
• Knowledge of data governance, data quality, metadata management, data lineage, and data security principles.
• Exposure to authentication and governance tools such as LDAP, OAuth, Keycloak, OpenMetadata, or similar solutions.
• Strong analytical, problem-solving, stakeholder management, and communication skills.
• Experience in financial services, capital markets, or large enterprise environments is an advantage.
• Relevant certifications in Agile, Scrum, PMP, PRINCE2, cloud, or data-related disciplines are preferred.