Overview
Full Time
Skills
Adaptability
Equities
Health Care
Research
Collaboration
Data Warehouse
Quantitative Research
Decision-making
Python
SQL
Software Engineering
Warehouse
Snow Flake Schema
Apache Spark
Amazon Web Services
Dashboard
Job Details
About Longaeva Partners
Longaeva: Pronounced "long-AY-vuh", our name is rooted in meaning! We are named after one of the oldest and most resilient living species, the longaeva pine. It represents longevity, adaptability, and persistence. It thrives in extreme conditions and has adapted for thousands of years in harsh environments. We hope to do the same, delivering positive, risk-adjusted returns to our investors in harsh and varied market conditions. We are a New York based hedge fund with a global investment mandate focusing on long duration investing across long/short public equities and late-stage private deals. Peter Goodwin is our founder and CIO, bringing almost 20 years of investing experience across the healthcare, consumer and TMT sectors. We are a high conviction, ideas driven firm built on a foundation of high performing product specialists and an intense commitment to primary research and data.
Overview
We are looking for a Software Engineer with a demonstrated interest and history working in an investment firm's Risk function. You will join Longaeva's Data Platform team and collaborate closely with both our Head of Technology and our Head of Quantitative Research/Risk. You will help build world-class solutions and applications that power crucial decisions throughout our hedge fund. We are looking for an open-minded, deep thinker who is passionate about building systems at scale. You will help build a world-class risk function through an approach rooted in ingesting multiple data sources, supporting the creation of tools to analyze, and disseminate information to our large team of investors.
Responsibilities
The Data Platform team manages data pipelines, web scrapes, data warehouse, and data models across organization. You'll join a team of very smart and highly dedicated individuals to build next-gen greenfield data platform for our hedge fund.
As a Software Engineer, you will apply your technical expertise to build processes that support our Quantitative Research/Risk team. You will design end-to-end solutions from the building of data pipelines, to the ingestion and analysis of data, to the packaging and dissemination of information directly to our investment team via e-mail, dashboard visualizations, and external platform providers. You will be instrumental in helping build and maintain systems that help decision-making, knowledge capture, and the maximization of alpha capture.
Required Qualifications
Expert knowledge of Python is required. Proficiency with SQL.
3+ years deep software engineering experience, building production data pipelines and warehousing solutions.
Experience building scalable data pipelines using Snowflake, Spark, dbt, Iceberg, and AWS.
Experience building APIs and highly scalable data platforms.
Experience building visualizations and interactive dashboards is preferred.
Familiarity with or a deep interest in an investment firm's risk function.
Ability to communicate technical concepts to diverse audiences.
Longaeva: Pronounced "long-AY-vuh", our name is rooted in meaning! We are named after one of the oldest and most resilient living species, the longaeva pine. It represents longevity, adaptability, and persistence. It thrives in extreme conditions and has adapted for thousands of years in harsh environments. We hope to do the same, delivering positive, risk-adjusted returns to our investors in harsh and varied market conditions. We are a New York based hedge fund with a global investment mandate focusing on long duration investing across long/short public equities and late-stage private deals. Peter Goodwin is our founder and CIO, bringing almost 20 years of investing experience across the healthcare, consumer and TMT sectors. We are a high conviction, ideas driven firm built on a foundation of high performing product specialists and an intense commitment to primary research and data.
Overview
We are looking for a Software Engineer with a demonstrated interest and history working in an investment firm's Risk function. You will join Longaeva's Data Platform team and collaborate closely with both our Head of Technology and our Head of Quantitative Research/Risk. You will help build world-class solutions and applications that power crucial decisions throughout our hedge fund. We are looking for an open-minded, deep thinker who is passionate about building systems at scale. You will help build a world-class risk function through an approach rooted in ingesting multiple data sources, supporting the creation of tools to analyze, and disseminate information to our large team of investors.
Responsibilities
The Data Platform team manages data pipelines, web scrapes, data warehouse, and data models across organization. You'll join a team of very smart and highly dedicated individuals to build next-gen greenfield data platform for our hedge fund.
As a Software Engineer, you will apply your technical expertise to build processes that support our Quantitative Research/Risk team. You will design end-to-end solutions from the building of data pipelines, to the ingestion and analysis of data, to the packaging and dissemination of information directly to our investment team via e-mail, dashboard visualizations, and external platform providers. You will be instrumental in helping build and maintain systems that help decision-making, knowledge capture, and the maximization of alpha capture.
Required Qualifications
Expert knowledge of Python is required. Proficiency with SQL.
3+ years deep software engineering experience, building production data pipelines and warehousing solutions.
Experience building scalable data pipelines using Snowflake, Spark, dbt, Iceberg, and AWS.
Experience building APIs and highly scalable data platforms.
Experience building visualizations and interactive dashboards is preferred.
Familiarity with or a deep interest in an investment firm's risk function.
Ability to communicate technical concepts to diverse audiences.
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