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Tier-1 brand, metro location, and broad analytics skillset increase candidate competition significantly.
Core analytics engineering skills are transferable, though financial services experience is a preferred plus.
Explicit 2+ years requirement plus SQL and preferred elite degrees makes screening moderately strict.
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Develop and maintain data transformations, curated datasets, and analytics-ready tables to support reporting and analysis across investment platforms.
Build and enhance dashboards and reports using BI tools like Power BI or Sigma, supporting business areas including Portfolio Management, Risk, Operations, Finance, and Investor Relations.
Support AI-enabled analytics initiatives by preparing high-quality data inputs and applying best practices around data quality, explainability, and governance.
Minimum 2+ years of experience in data analytics, analytics engineering, BI, or data engineering.
Strong SQL skills with experience working on analytical datasets.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field; MBA from tier I institute (IIT/NIT/BITS or IIM/ISB/XLRI) preferred.
Experience in financial services (credit or asset management) is a plus; exposure to cloud data platforms (Azure, Snowflake) and BI tools (Power BI, Tableau, Qlik) preferred.
Experience working within analytics or data engineering roles supporting investment, credit, or asset management functions, able to translate business needs into technical solutions.
Comfortable collaborating with senior analytics engineers, business users, and multi-location teams to deliver analytics-ready datasets and dashboards.
Familiarity or interest in AI-enabled analytics, data governance, and advanced analytics practices tailored to financial services contexts.