Sam Jakshtis

Analytics Engineer

Python | DBT | SQL | Analytics Engineering | Proptech

I am an Analytics Engineer specializing in the architecture of high-stakes financial and real estate data systems. Expert in leveraging the modern data stack (DBT, Python, SQL) to transform raw, unstructured data into institutional-grade assets. Proven track record of partnering with C-suite leadership and cross-functional teams to drive data-driven insights for funds and large-scale asset portfolios. Outside of code, I am also a part-time farmer, raising cattle, pigs, and chickens on my family farm.

Experience

Analytics Engineer

Arrived

Jan 2026 - Present | Remote

Reporting directly to the CTO to lead the evolution of the data modeling layer, ensuring data integrity for fractional real estate investment products.
Architecting scalable data schemas to support rapid growth and preparing for a transition into a management role overseeing the data function.

M.B.A. Candidate

Massachusetts Institute of Technology

Sept 2024 - Dec 2025 | Cambridge, MA

M.B.A. with a focus in real estate and data systems.

Financial Data Engineer

Darwin Homes

Sept 2023 - Jan 2024 | Remote

Designed and supported Finance and Accounting reporting using SQL and Python, improving reporting accuracy and reducing month-end closing time for stakeholders.
Orchestrated scalable ETL workflows using Fivetran and Airbyte, resulting in 99.9% data uptime across distributed data stores.
Partnered with Finance/FP&A for the parent hedge fund to translate needs into DBT jobs, enabling real-time quantitative analysis for critical portfolio decision-making.

Data Manager

LandVest

August 2021 - August 2023 | Boston, MA

Architected data workflows for $10MM+ asset portfolios, transforming unstructured property data into standardized datasets used for institutional fund reporting.
Automated quarterly reporting pipelines using Python and SQL, which eliminated manual aggregation and accelerated the delivery of market intelligence publications.
Developed financial models to simulate asset performance, providing actionable insights that directly influenced strategic acquisition and divestment decisions.

Backend Engineer

Doorkee

June 2020 - August 2021 | New York City, NY

Engineered optimized pricing models for 1,000+ unit property management firms, directly increasing rental income yields and reducing vacancy rates through data-driven price elasticity.
Analyzed NYC apartment trends using Machine Learning, improving the accuracy of market movement forecasts for internal team members.
Streamlined internal workflows through data analytics to improve company-wide data accessibility.