Senior Analyst (Data Engineering)

In this role, you will help transform manual and fragmented processes into efficient, data-driven and scalable digital solutions. You will bridge business needs and technology execution, using AI, data and automation to improve decision-making and operational performance. Working closely with business stakeholders, DIT teams and vendors, you will support end-to-end digitalization projects that deliver measurable and sustainable business value.

Key Responsibilities

Digitalization, AI, Data & Process Improvements

• Assist in the discovery, design, and delivery of digitalization initiatives targeting internal operations and process automation.
• Be part of the team in engaging with business stakeholders to uncover pain points and translate them into practical, scalable technical solutions.
• Codify and document critical business processes.
• Assist in building data pipelines, internal tools, and automation workflows — making build-vs-buy decisions pragmatically.
• Assist to evaluate and manage third-party vendors and platforms where appropriate, ensuring fit-for-purpose outcomes.
• Assist to drive AI-powered initiatives including process automation, predictive analytics, and LLM-based tooling where relevant.
• Assist to define and uphold engineering standards, documentation practices, and solution governance across projects.
• Be part of the digitalization team, staying current with emerging technologies and bringing forward-thinking ideas to the table.

Requirements:

Qualifications & Experience

• Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Engineering or a related technical discipline.
• At least 4 years of relevant experience in software engineering, data engineering, IT applications or analytics-related projects.
• Experience contributing to digitalization or transformation projects from inception to production.
• Experience with requirements gathering, identifying business needs and recommending solutions that deliver stakeholder value.
• Experience applying AI to business problems and exposure to operational or back-office processes are advantageous.
• Relevant certifications such as Azure Data Engineer, Databricks Certified Associate, PMP, PRINCE2, CBAP or ITIL are advantageous.

Technical Skills

• Proficiency in at least one modern programming language, such as Python, Java or TypeScript.
• Strong SQL skills, including manipulation and transformation of datasets and an understanding of SQL tuning.
• Knowledge of ETL/ELT pipelines, data modelling and integration across systems.
• Hands-on experience with Power BI or other data visualisation tools.
• Experience with APIs, automation and data platforms, preferably Databricks, is advantageous.
• Familiarity with cloud platforms, preferably Azure, modern DevOps practices, SaaS tools and enterprise systems is advantageous.

Skills & Attributes

• Strong analytical and problem-solving skills, with an ability to identify root causes rather than address symptoms only.
• Creative and resourceful, with the ability to propose practical solutions within resource constraints.
• Effective communication skills and the ability to translate technical concepts for non-technical stakeholders.
• Self-directed, detail-oriented and comfortable managing ambiguity in a dynamic environment.
• Strong sense of ownership and a genuine passion for using technology to make work smarter and more efficient.