Head - Data Analysis - Asset Management

Overview

Lead the data analysis capability for Asset Management, setting standards, building a community of practice, and overseeing data engineering and data platform reliability in India, while owning investment data products.

What you'll do

• Establish the standards, methodologies and operating model for data analysis and Data Platform Reliability, ensuring consistent, high-quality outcomes across all strategic initiatives.
• Build a community of practice across data analysis, strengthening capability, building reusable assets, knowledge sharing and continuous improvement.
• Develop, coach and mentor Lead and Senior Data Analysts and Data Engineers, raising technical depth, domain fluency and stakeholder impact; define structure, role design, career pathways, skills framework and succession.
• Own the analysis and definition of investment data products, ensuring alignment with investment, client, risk, regulatory, ESG and operational objectives across public and private markets.
• Materially improve data product delivery speed and predictability through clearer demand intake, prioritisation, product-aligned squads, reusable patterns, automation and reduction of rework.
• Champion data product thinking and data mesh principles across the Asset Management data estate.
• Define and maintain data contracts; translate business needs into technical analysis, data definitions, transformation logic, schema definitions, business rules, critical data elements and lineage, ensuring traceability and enterprise-wide reuse of investment data.
• Partner with data domain product owners to shape strategic data roadmaps, prioritise investment data capabilities and translate business outcomes into scalable, governed data solutions.
• Provide hands-on technical guidance to the team, including complex SQL, data models, transformation logic, reconciliations, test approach and analytical outputs; set the bar for quality.
• Oversee the data engineering and data platform reliability capability in India covering pipelines, ingestion, transformation, APIs and data services, ensuring solutions are secure, resilient, observable, performant and cost-effective.
• Contribute to platform and tooling choices across the modern data stack (Snowflake, Azure data services, Databricks, orchestration, data catalogue, lineage and data quality tooling) in partnership with Architecture and the Head of Engineering.
• Embed engineering and data platform reliability discipline, including CI/CD, automated testing, data-quality-as-code, environment management, release control and production support practices.
• Collaborate across Data Quality, Data Governance and Data Ownership initiatives, ensuring data is trusted, controlled, governed and fit for purpose across the investment data ecosystem.
• Define and govern data standards, metadata, data models, data quality controls and issue management, including measurable data quality KPIs and remediation accountability with data owners and stewards.
• Operate as a member of the India Asset Management Technology leadership team and the Global Data, AI & Analytics Platform leadership team, making effective decisions, collaborating across silos, speaking up and taking personal accountability.
• Engage senior UK and India stakeholders with clear, evidence-based communication on capability, delivery confidence, risks, trade-offs and value realised.
• Implement and monitor KPIs for analysis quality, delivery throughput, cycle time, data quality and stakeholder satisfaction, using data to drive decisions and continuous improvement.
• Leverage AI-enabled analysis and engineering responsibly, including prompt engineering, AI-assisted SQL, documentation, testing and insight generation, in line with Responsible AI standards.
• Inspire the team to deliver exceptional performance by connecting the purpose of their work to customer, client and colleague outcomes.
• To work collaboratively with colleagues and take personal accountability to maintain and enhance controls you are responsible for to support improvement of the overall control environment, customers outcomes and a reduction in M&G plc's operational risk.

Details

• Location: Mumbai.