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Grantham Mayo Van Otterloo Co
,
London, Greater London
Research Data Warehouse Developer
Overview
Job Description
Company Profile Founded in 1977, GMO is a private partnership committed to delivering superior investment performance and advice to our clients. We offer strategies where we believe we are positioned to add the greatest value for our investors. These include multi-asset class portfolios as well as dedicated equity, fixed income, and absolute return offerings, many of which employ the firm's proprietary 7-year asset class forecasting framework. Our client base is comprised primarily of institutions, including corporate and public defined benefit and defined contribution retirement plans, endowments, foundations, and financial intermediaries. GMO, whose sole business is investment management, employs approximately 475 people worldwide and is headquartered in Boston with offices in San Francisco, London, Amsterdam, Sydney, and Singapore. We manage roughly $70 billion in client assets using a combination of top-down and bottom-up approaches that blend traditional fundamental insights with innovative quantitative methods to identify undervalued asset classes and securities. Our valuation-based approach embeds several key factors, including: a long-term investment horizon, discipline, conviction, and a commitment to research. Our research emphasizes not only identifying and exploiting pricing dislocations but also understanding the long-term drivers of return in the markets in which we invest. We are known for our candor in sharing our views with clients and for our willingness to take bold, differentiated positions when opportunities warrant. Position Overview GMO has undertaken a strategic, firm-wide initiative to build a next generation research and investment platform. Leveraging a blend of traditional RDBMS and Big Data technologies, this initiative will provide a collaboration platform to help our investment teams continue to set the standard for investment performance for our clients. We are seeking an experienced Data Warehouse (DW) Engineer to join the SQL DW team to help refactoring the existing platform and gradually help build and integrate the future platform and its leading-edge capabilities. Experience in the financial industry is preferred, but we are open to experts from any industry with an interest in learning about investment management. Experience and Expectation: * Minimum 6-7 years of DW engineering experience, and at least 1 - 3 years hands-on experience with scale-out technologies * Must be result-oriented; takes commitments and deadlines seriously * Willing to work diligently and deliver solutions on schedule and within given budget parameters * Self-starter, able to work with minimal supervision and independently Minimum 6-7 years of DW engineering experience, and at least 1 - 3 years hands-on experience with scale-out technologies Must be result-oriented; takes commitments and deadlines seriously Willing to work diligently and deliver solutions on schedule and within given budget parameters Self-starter, able to work with minimal supervision and independently Hands-on experience and knowledge with the following : * Strong, set-based T-SQL programming skills and deep-dive knowledge of SQL internals * Experience with SQL Server performance tuning and execution plans * Strong understanding of DW concepts such as persistent staging, date packing, SLCD, map and reducing, time series objects * Implemented efficient ETL and ELT processes for large data sets, preferably with market and trading data related providers * Building Big Data solutions using Hadoop and Spark or equivalent DW scale-out solutions * Production experience with public clouds such as Azure (preferred) or AWS * Must be detail-oriented and able to prioritize work and effectively manage multiple tasks * Possess solid knowledge and experience with relevant programming languages and tools such as Scala, Python, unit test frameworks, CI/CD, C#, .NET framework * Hands-on experience with at least one NoSQL database (e.g., MongoDB, Cassandra, HBase, CouchDB, BigTable, DynamoDB, CosmosDB) Strong, set-based T-SQL programming skills and deep-dive knowledge of SQL internals Experience with SQL Server performance tuning and execution plans Strong understanding of DW concepts such as persistent staging, date packing, SLCD, map and reducing, time series objects Implemented efficient ETL and ELT processes for large data sets, preferably with market and trading data related providers Building Big ...