Senior Manager Data Analyst-Investment Management​/Asset Management

Location: Bengaluru

Your Skills and Experience

· At least 12-15 years exp as a business/technical/data analyst within technology and/or business changes within the financial services /asset management industry.

· 8-9 years as business/technical/data analyst adhering to agile methodology, delivering data solutions using industry leading data platforms such as Snowflake, State Street Alpha Data, Refinitiv Eikon, Sim Corp Dimension, Black Rock Aladdin, Fact Set etc.

· Proven experience. of delivering data driven business outcomes using industry leading data platforms such as Snowflake.

· Excellent knowledge of data life cycle that drives Middle and Back Office capabilities such as trade execution, matching, confirmation, trade settlement, record keeping, accounting, fund & cash positions, custody, collaterals/margin movements, corporate actions, derivations and calculations such as holiday handling, portfolio turnover rates, funds of funds look through .

· In Depth expertise in data and calculations across the investment industry covering the below.

· Asset-specific data:
This includes data related to financial instruments reference data like asset specifications, maintenance records, usage history, and depreciation schedules.

· Market data:
This includes data like security prices, exchange rates, index constituents and licensing restrictions on them.

· Risk data:
This includes data related to risk factors such as market risk, credit risk, operational risk, and compliance risk.

· ESG data:
This includes data related to ESG Ratings, Research, Sustainbility.

· Should possess Problem Solving, Attention to detail, Critical thinking.

· Technical

Skills:

Excellent hands-on SQL, Advanced Excel, Python, Data Visualization platforms, like OBIEE, Power BI, Tableau etc, ML (optional) and proven experience and knowledge of data solutions.

· Knowledge of data management, data governance, and data engineering practices

· Hands on experience on data modelling techniques such as dimensional, data vault etc.

· Willingness to own and drive things, collaboration across business and tech stakeholders.