Middle Office Data Engineering and Quality_Vice President_Product Support & Services IM

Proficient in data validation, data cleansing, and data governance.

Experience in investment management across pooled vehicles, SMAs, and institutional mandates.

Demonstrated understanding of investment and trade lifecycle, with focus on portfolio tax lot level recordkeeping inputs (reference data, marker trades, prices, corporate actions, accruals, amortization, etc.).

Familiarity with a full range of financial products, including public and private instruments, and asset classes (e.g., equity, fixed, derivatives, loans).

AI savvy and experienced with leading process improvements and transformation. Change management experienced. Experienced in leveraging python & LLM libraries for faster adoption process automation concepts, experienced in leveraging API for data transfers, experienced in NLP / OCR solution implementation. Alteryx workflow experience for data conversion and data / rule optimization & conversion. Experienced in cloud strategy especially from data use and transfer perspective. Databricks AI module experience will be value add

Lead & supported solutions which involved, client & trade lifecycle automation involving AI solutions

Demonstrated leading / supporting key change the bank initiatives and ability to articulate current and target operating models by leveraging tools and technologies

Experience with data quality tools, dashboards, APIs to support real-time data validation and exception handling.

Strong technology (pro dev and low code) experience, with a track record of developing data-driven platforms, dashboards, and automated controls

Strong analysis and analytical skills to perform root cause analysis, data lineage, exception handling, and process optimization.

Demonstrated ability to synthesis data for MI reporting on key performance indicators and other portfolio accounting data as inputs into middle office data health and identifying areas for operational optimization.

Experience with Data Quality platforms (e.g. Pan DQ, Informatica, PEGA Exception Management) & Business Intelligence Tools (e.g. Alteryx, PowerBI, etc)

Experienced to lead & run with multiple workstreams associated to Data quality which involves multiple senior stakeholders spread across operations, technology & Data functions. To be able to drive Data quality process and outcomes.