Consultant Conversion: Dir, P4, Lead Software Eng

At Morgan Stanley, we advise, originate trade, manage, and distribute capital for governments, institutions, and individuals, and always do so with a standard of excellence. We are a leading global financial services firm that conducts its business through three principal business segments-Institutional Securities, Wealth Management (WM), and Investment Management. The Firm's employees serve clients worldwide from more than 1,200 offices in 43 countries.

Our WM business is one of the largest in the world with more than $2 trillion in client assets, $73 billion in lending balances, and nearly 16,000 Financial Advisors in 600+ offices across the U.S. Our Financial Advisors focus on delivering timely, customized solutions and services that help clients meet their financial and life goals. Our offering includes brokerage and investment advisory services, financial and wealth planning, access to credit and lending, cash management, annuities and insurance, and retirement services.

As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence, and strong team ethic. Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.


Department Profile

Wealth Management Product Technology (WMPT) is a dynamic and fast-paced area within the Firm's WM Technology Division. We are responsible for creating innovative technology solutions for the Private Banking Group (PBG), one of the strategic growth areas of the Firm, providing cash management and lending products and services to our WM clients. This includes state-of-the-art technology for a nationwide network of Private Bankers and product specialists who work with Financial Advisors to provide access to products and services such as online banking, cards, deposit products, residential mortgages, securities-based loans, and tailored lending. If you are an exceptional individual who is interested in solving complex problems and building sophisticated solutions in a dynamic team environment, WMPT is the place for you.

Position Description:
As part of strategy to design and implement industry leading applications Morgan Stanley WMPT team is looking for a Data Engineer with good experience on Hadoop ecosystem to join a technologically advanced team. Candidate must have expertise in design and development of Hadoop ETL, including Hive queries, performance tuning, archiving, etc., using Shell, Python, SQL and ETL tools. Candidate will interface on a regular basis with other teams including other internal IT teams across Wealth Management, BA team, QA team, and global development team. To be successful, the role will require the individual to understand the financial technology landscape, and to offer creative solutions that integrate current capabilities, vendor capabilities, proprietary system builds, and the ability to adapt to changing business requirements.


What you will do in the role:

• Work in an Agile Squad as a Data Engineer developer
• Review code and contribute to design discussions.
• Ensure high quality of deliverables while enforcing development best practices.
• Adhere to application development guidelines and help improve the guidelines.
• Understand and implement security guidelines and best practices.
• Troubleshoot and resolve errors or critical issues.
• Mentor junior developers and share knowledge with the team.
• Demonstrate features built as part of the sprint to business stakeholders.
• Actively contribute and participate in sprint grooming and planning discussions, daily stand-ups, and Agile ceremonies
• Work on PoCs to adopt newer technologies and frameworks.

What You will bring to the role:

• Proficiency in one or more general purpose big data languages - Hadoop, Python, Hive, HDFS and Spark
• 8+ years of experience with the technical analysis and design, development and implementation of Data Lake and Data Warehouse solutions.
• Experience data modelling and transformation of large-scale data sources using SQL, Hadoop, Spark, Hive, Snowflake, Databricks, Teradata or other Big Data technologies.
• 5+ years of experience in Hadoop, PySpark and Big data technologies.
• 5+ years' experience in relational database such as DB2, Sql Server or other RDBMS
• Strong UNIX Shell scripting and Python experience to support data warehousing solutions.
• DDL and DML writing skills are essential as well as being able to write complex SQLs for data analysis.
• Create high quality and optimized stored procedures and queries.
• Data warehousing concepts (Fa