Responsible for leveraging data, analytics, automation, and AI-enabled tools to deliver high-quality, scalable business solutions. The role acts as a subject matter expert across analytics platforms, driving insight generation, operational efficiency, and data-driven decision-making. This position also plays a key enablement role—upskilling colleagues, promoting self-service analytics, embedding best practices, and serving as a point of escalation for complex analytics, automation, and AI-assisted solutions.
Key Accountabilities and main responsibilities
Strategic Focus
- Understand business needs, gather requirements, and develop bespoke analytics solutions, dashboards and data products aligned to key business objectives.
- Identify and implement opportunities to apply AI, prompt engineering and intelligent automation to enhance reporting, forecasting, and decision-making processes.
- Develop advanced BI and automation solutions using Alteryx, Power Apps, Fabric, and LLM-enhanced workflows.
- Drive uplift in data governance practices, data quality, and metadata management, including adoption of platforms like OneTrust for data cataloguing and retention (GDPR).
- Partner with business leaders to identify new use cases where data and AI can improve operational efficiency, customer experience, and risk insight.
- Contribute to enterprise strategies on self-service analytics, responsible AI, and democratisation of insight.
Operational Management
- Build scalable analytical models, simulations, and automated workflows using Alteryx, Microsoft pipelines (Fabric, Power Apps).
- Design, develop, validate, and maintain ETL/ELT processes and data integrations aligned to architectural and governance standards.
- Improve operational reporting through enhanced quality, reduced lead times, and AI-supported summarisation.
- Prompt Engineering for Analytics:
- Design and iterate prompts to convert dashboards, SQL output, and tabular data into executive-ready summaries, insights, and recommendations.
- Use LLMs (Copilot, ChatGPT) to automate recurring reports, detect anomalies, and generate week-over-week insights through structured prompt workflows.
- Data-to-Decision Translation:
- Tailor AI-generated outputs into stakeholder-specific formats (email briefings, slide bullets, risk callouts) to bridge the gap between raw metrics and decision-makers.
- Script Decoding & Logic Translation:
- Apply AI tools to translate SQL/Python logic into plain English to support onboarding, knowledge sharing, and cross-functional understanding.
- Self-Service BI Expansion:
- Build reusable prompt templates into dashboards and BI tools, enabling non-technical users to ask natural-language questions and obtain meaningful insights.
- Document systems, data sources, metrics, and processes to ensure transparency, continuity, and auditability.
- Provide analytical support in interpreting, reporting, visualising, and presenting insights to stakeholders.
People Leadership
- Build strong relationships across the business to uplift digital capability, promote adoption of analytics, automation, and AI tools.
- Provide coaching, training, and support to business users on reporting tools, dashboards, and safe, effective use of AI copilots and BI features.
- Champion a culture of continuous improvement, innovation, and responsible use of AI-augmented analytics.
- Role-model MUFG Market Services values and contribute to a high-performing, collaborative environment.
Governance & Risk
- Define and implement policies, processes, and standards for responsible management of data, including capture, storage, architecture, security, integration, reporting, and analytics.
- Embed strong governance controls into analytics and AI-enabled workflows (documentation, lineage, validation, access management, auditability).
- Support model and AI risk management requirements to ensure LLM-powered processes are transparent, ethical, and compliant with regulatory frameworks.
- Provide guidance on data quality, stewardship, and risk identification, and contribute to development of a unified approach to enterprise dataset management.
The above list of key accountabilities is not an exhaustive list and may change from time-to-time based on business needs.
Experience & Personal Attributes
- Data & Analytics Experience
- Extensive hands-on expertise with Alteryx Designer, Alteryx Server, and ideally Alteryx One, with proven ability to design scalable, controlled, and auditable workflows.
- Strong skills in Data Engineering, including ETL/ELT development, optimisation, and data pipeline automation using MySQL, Alteryx, and Azure technologies.
- Solid understanding of data warehouse architecture, including dimensional modelling, semantic modelling, and performance optimisation.
- Experience designing, deploying, and maintaining analytics solutions in Azure, including Azure Synapse Analytics, Data Lake, and Fabric components.
- Expertise in building business-facing Power BI dashboards, reports, semantic models, and integrating them with automated workflows through Power Apps
- Experience in functional design and delivery of enterprise BI and analytics solutions across complex business environments.
- Strong working knowledge of testing methodology, change management and release management, ensuring high-quality, controlled delivery of data products.
- Experience in developing and managing enterprise data warehouse environments, including metadata management, lineage documentation, and governance alignment.
AI Skills
- Experience using AI-assisted tools (e.g., Copilot, ChatGPT) for:
- Insight summarisation
- Logic translation (SQL/Python → plain language)
- Prompt-engineered reporting and anomaly detection
- Automating insight generation and stakeholder communications
- Ability to embed AI features into BI tools to uplift self-service analytics and reduce dependency on specialist teams.
Professional Experience
- Bachelor’s degree in Engineering, Technology, Computer Applications, or related discipline (B.E/B.Tech/MCA).
- 5 - 7 years of experience, preferably within the BFSI sector, with exposure to risk, controls, operations, and customer analytics.
- Proven success building enterprise-level dashboards, reporting environments, and data-driven solutions using Power BI, Power Automate, Alteryx.
- Recognised Microsoft, Alteryx certifications or best-in-class demonstrable expertise.
- Experience translating business requirements into robust data solutions, with strong stakeholder engagement and cross-functional collaboration.
- Knowledge of Single Customer View (SCV) and financial industry data structures is highly desirable.
