Middle Office Data Engineering and Quality_Director_Core Services

Morgan Stanley•Campus, IL

18h

About The Position

We are seeking a strategic, data-driven Middle Office Data Engineering and Quality - Director to lead the build and evolve a best-in-class Data Quality and Engineering function in India. This role sits within the Public Markets Middle Office and is pivotal to ensuring data accuracy, transparency, and operational readiness across the firm's transaction lifecycle in support of MSIM clients, investment teams and traders, and other essential uses of this data. The successful candidate will be an innovative data science professional, who will develop quality control checks and insights to mitigate data quality issues, identify anomalies in data for research, and continuously improve upon the process to expand across a complex data set. This position will partner closely with the Middle Office functional teams to establish and evolve the cross-platform data quality framework and controls for transaction lifecycle data to support efficient trade processing. In the Operations division, we partner with business units across the Firm to support financial transactions, devise and implement effective controls and develop client relationships. This is a Team Supervisor position at Director level within the within Core Services, which is responsible for performing and managing product-agnostic and centralized operational services across several businesses and products Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world. What you'll do in the role: Operational Data Quality Framework & Controls: Own data quality framework for cross platform transaction lifecycle management data Lead cross platform alignment for integrated controls and monitoring and ability to navigate business matters. Develop, maintain, and operationalize data quality controls across the transaction lifecycle Align with enterprise data strategy/governance initiatives to ensure implementation within Middle Office. Maintain robust data validation and exception monitoring processes to ensure cross platform completeness, accuracy, and timeliness cross. Support research and triage of data exceptions, enabling scalable issue identification, mitigation and/or resolution, and escalation. Provide high-touch leadership and accountability of complex and sensitive data sets. Document business requirements and use cases for data-related projects Ensure proactive, high-quality outcomes for clients and investment teams, and other data consumers of MSIM's books and records. Build and implement data-driven platforms, dashboards, and automated controls, including managing change control process and participate in user acceptance testing (UAT) activities as required. Deliver and manage KPI dashboards, trend analysis, and exception reporting to senior stakeholders and data governance forums. > BS/BA degree required. WHAT YOU CAN EXPECT FROM MORGAN STANLEY: At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents. At Morgan Stanley, we advise, originate, trade, manage and distribute capital for people, governments and institutions, always with a standard of excellence and guided by our core values. Morgan Stanley is dedicated to providing first-class service to our clients, in a way that reflects our commitment to creating a more sustainable future and fostering stronger communities around the world. In each line of business, we strive to demonstrate our belief in the power of transformative thinking, innovative strategies and leading-edge solutions—and in the ability of capital to work for the benefit of all society. What We Do

Requirements

7+ years of experience in Investment Operations, Data Management, or Middle Office data and analytics at a global asset manager or financial services firm.
A strong understanding of data quality principles, including accuracy, completeness, consistency, and timeliness.
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 cross platform data sets and outcomes (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 experience with leading process improvements and transformation.
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. PanDQ, Informatica, PEGA Exception Management) & Business Intelligence Tools (e.g. Alteryx, PowerBI, etc...)
BS/BA degree required.

Responsibilities

Own data quality framework for cross platform transaction lifecycle management data
Lead cross platform alignment for integrated controls and monitoring and ability to navigate business matters.
Develop, maintain, and operationalize data quality controls across the transaction lifecycle
Align with enterprise data strategy/governance initiatives to ensure implementation within Middle Office.
Maintain robust data validation and exception monitoring processes to ensure cross platform completeness, accuracy, and timeliness cross.
Support research and triage of data exceptions, enabling scalable issue identification, mitigation and/or resolution, and escalation.
Provide high-touch leadership and accountability of complex and sensitive data sets.
Document business requirements and use cases for data-related projects
Ensure proactive, high-quality outcomes for clients and investment teams, and other data consumers of MSIM's books and records.
Build and implement data-driven platforms, dashboards, and automated controls, including managing change control process and participate in user acceptance testing (UAT) activities as required.
Deliver and manage KPI dashboards, trend analysis, and exception reporting to senior stakeholders and data governance forums.