Data Analytics Senior Specialist

Overview

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.
• Insight Automation:
• 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.