GMO
Enterprise Data Engineer
GMO, Boston, Massachusetts, us, 02298
Company Profile
Founded in 1977, GMO is a global investment manager committed to delivering superior long-term investment performance and advice to our clients. We offer strategies and solutions where we believe we are positioned to add the greatest value for our investors. These include multi-asset class, equity, fixed income, and alternative offerings.
We manage approximately $60bn for a client base that includes many of the world’s most sophisticated institutions, financial intermediaries, and private clients. Industry-wide, we are well known for our focus on valuation-based investing, willingness to take bold positions when conditions warrant, and candid and academically rigorous thought leadership. Jeremy Grantham, GMO’s Co-Founder and Long-Term Investment Strategist, is renowned as an expert in identifying speculative investment bubbles and also as a leading climate investor and advocate.
GMO is privately owned and employs over 430 people worldwide. Headquartered in Boston, we also have offices in San Francisco, London, Amsterdam, Singapore, Sydney, and Tokyo (a representative office). Our company-wide culture emphasizes commitment to clients, intellectual curiosity, and open debate. We celebrate and respect our differences, while embracing and valuing what each of us brings to work, as we know that diverse teams in an inclusive, caring environment achieve higher engagement and better client results.
Position Overview
The Enterprise Data Engineering Team is responsible for the development and support of GMO’s critical data processing and warehousing applications. This team consists of data engineers whose key functions include database development, system integration, and production support. Engineers are responsible for implementation and maintenance of multiple proprietary databases, with a focus on an Azure Synapse Enterprise Data Warehouse. The candidate will participate in an agile development lifecycle. The role offers the candidate an opportunity to innovate while working with seasoned engineers in support of GMO’s key business groups.
Primary Responsibilities:
Design and implement SQL and Python solutions for GMO’s Portfolio Management, Operations, Marketing, and Client Reporting teamsMaintain an Azure Synapse Enterprise Data WarehouseMigrate existing systems to a cloud environmentImplement optimal data modeling and access patterns to allow for performant but cost-effective data useSupport the production processing of data within the Enterprise data ecosystem
Mandatory:
2-5 years of SQL and Python programming experienceExperience and interest in working in the financial services industryExperience with cloud-based platforms such as Microsoft Azure or AWSFamiliarity with distributed enterprise applicationsUnderstanding of Agile practicesUndergraduate degree in Computer Science
Preferred:
Experience with Azure data platforms including Synapse, SQL Database, Data Factory and Data LakeExperience working with data (files, rest APIs, databases) in PythonExperience migrating distributed applications to a cloud-based platformExperience working with data warehousing technologiesExperience working with financial data systemsFamiliarity with NeoXam DataHub helpful but not required
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Founded in 1977, GMO is a global investment manager committed to delivering superior long-term investment performance and advice to our clients. We offer strategies and solutions where we believe we are positioned to add the greatest value for our investors. These include multi-asset class, equity, fixed income, and alternative offerings.
We manage approximately $60bn for a client base that includes many of the world’s most sophisticated institutions, financial intermediaries, and private clients. Industry-wide, we are well known for our focus on valuation-based investing, willingness to take bold positions when conditions warrant, and candid and academically rigorous thought leadership. Jeremy Grantham, GMO’s Co-Founder and Long-Term Investment Strategist, is renowned as an expert in identifying speculative investment bubbles and also as a leading climate investor and advocate.
GMO is privately owned and employs over 430 people worldwide. Headquartered in Boston, we also have offices in San Francisco, London, Amsterdam, Singapore, Sydney, and Tokyo (a representative office). Our company-wide culture emphasizes commitment to clients, intellectual curiosity, and open debate. We celebrate and respect our differences, while embracing and valuing what each of us brings to work, as we know that diverse teams in an inclusive, caring environment achieve higher engagement and better client results.
Position Overview
The Enterprise Data Engineering Team is responsible for the development and support of GMO’s critical data processing and warehousing applications. This team consists of data engineers whose key functions include database development, system integration, and production support. Engineers are responsible for implementation and maintenance of multiple proprietary databases, with a focus on an Azure Synapse Enterprise Data Warehouse. The candidate will participate in an agile development lifecycle. The role offers the candidate an opportunity to innovate while working with seasoned engineers in support of GMO’s key business groups.
Primary Responsibilities:
Design and implement SQL and Python solutions for GMO’s Portfolio Management, Operations, Marketing, and Client Reporting teamsMaintain an Azure Synapse Enterprise Data WarehouseMigrate existing systems to a cloud environmentImplement optimal data modeling and access patterns to allow for performant but cost-effective data useSupport the production processing of data within the Enterprise data ecosystem
Mandatory:
2-5 years of SQL and Python programming experienceExperience and interest in working in the financial services industryExperience with cloud-based platforms such as Microsoft Azure or AWSFamiliarity with distributed enterprise applicationsUnderstanding of Agile practicesUndergraduate degree in Computer Science
Preferred:
Experience with Azure data platforms including Synapse, SQL Database, Data Factory and Data LakeExperience working with data (files, rest APIs, databases) in PythonExperience migrating distributed applications to a cloud-based platformExperience working with data warehousing technologiesExperience working with financial data systemsFamiliarity with NeoXam DataHub helpful but not required
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