About Longaeva PartnersLongaeva: 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 challenging environments. We hope to do the same, delivering positive, risk-adjusted returns to our investors, even in dynamic and demanding 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. Our founder and CIO, Peter Goodwin, bringing nearly 20 years of investing experience across the healthcare, consumer and TMT sectors.
We are a high-conviction, ideas-driven firm built on collaboration, rigorous primary research, and data-driven decision making.A core part of our approach is leveraging advanced artificial intelligence and technology to enhance our research, generate insights, and drive better investment outcomes. At Longaeva, you'll join a team that values intellectual curiosity, diverse viewpoints, and a shared commitment to uncovering differentiated investment opportunities.
OverviewWe are seeking a Senior Data Engineer with deep buy-side experience in data modeling and engineering core investment datasets: security master, reference data, positions, P&L, and related market data. In this role, you will design and build foundational data models and pipelines that power research, risk, and portfolio management across the firm. You will work closely with investment, risk, trading, data science, and technology teams to create a robust, flexible data platform and data warehouse that is the single source of truth for our investment ecosystem. Experience with alternative data (modeling and integrating it alongside traditional data) is a strong plus.
This is a hands-on engineering role for someone who loves data modeling, understands how a hedge fund "ticks" front-to-back, and wants to own critical production systems end-to-end. You will enable a best-in-class data engineering practice, drive the approach with which we model and use investment data, and build data APIs, backend systems, and data models that directly support portfolio managers, risk, trading, and alternative data research.
ResponsibilitiesThe Data Platform team manages data pipelines, web scrapes, the data warehouse, and data models across the organization. You'll join a team of very smart and highly dedicated individuals to build and maintain a next-gen, greenfield data platform for our hedge fund.
As a Senior Data Engineer, you will:
- Own core investment data domains, design and evolve data models for:
- Security master and instrument taxonomy across asset classes
- Reference data (identifiers, classifications, calendars, corporate actions)
- Transactions, positions, exposures, and holdings across portfolios and strategies
- P&L and returns (intraday and end-of-day, attribution-ready)
- Market data and benchmarks required for risk and performance
- Define and enforce data modeling standards (naming, normalization, SCD strategy, partitioning, performance)
- Build and operate production data pipelines
- Design, implement, and maintain scalable batch data pipelines to ingest, cleanse, normalize, and reconcile data from many internal and external data sources
- Implement robust data quality, lineage, and reconciliation processes for transactions, positions and P&L
- Continuously improve data by adding new sources, coding business rules, and producing new metrics that support investment, trading, and risk decisions
- Data products & APIs
- Build reusable data services and APIs that expose curated investment datasets to downstream consumers (portfolio managers, risk, quantitative research, dashboards, and external platform providers)
- Partner with our Quantitative Research/Risk team to package and disseminate data and analytics to the investment team via e-mail, dashboards, and integrated tools
Required Qualifications- 5+ years of deep software & data engineering experience, data modeling, and data architecture ideally on the buy side (hedge fund, asset manager, or multi-strategy platform)
- Expert deep knowledge of Python and SQL
- Proven experience building production-grade data pipelines and warehousing solutions
- Strong understanding and hands-on experience with core investment data domains: security master and reference data (identifiers, classifications, corporate actions), transactions, positions, holdings, and exposures, P&L and performance (including reconciliation concepts), market data and pricing
- Experience building scalable data pipelines and data platforms using Snowflake, Spark, dbt, Airflow, Dagster, and AWS (or equivalent cloud stack)
- Strong understanding of normalized and dimensional data modeling, partitioning/clustering, auditing, and performance tuning
- Demonstrated data quality mindset. Experience designing and implementing validation checks, reconciliation logic, and monitoring for positions and P&L
- Ability to communicate technical concepts clearly to diverse audiences (investors, risk, trading, data science, technology) and to document systems and data contracts
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