Sr. Data Engineer

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FarmTogether · San Francisco, CA

Engineering
Climate Change
Food & Agriculture
$110000 - $140000 Per Year
Posted 2 months ago

Redshift
Data Science
Python
SQL

Create a New Asset Class. Feed the Planet. Fight Climate Change.

FarmTogether is creating a technology-driven investment and trading platform for a brand new asset class - a $10 trillion global farmland market, previously only accessible to the largest institutional investors. This is a unique opportunity to join at the very beginning of this exciting journey and help grow a truly innovative financial product while also having an active role in battling climate change and creating food systems of the future.

Our vision is to provide all investors with access to farmland investments, and farmers and farmland owners with access to flexible and creative capital.

We are looking for a Sr. Data Engineer (US-based; Bay Area or Remote) who can be a key contributor in building out FarmTogether’s data infrastructure. In this role, you will use your full data engineering toolkit to design, build, maintain and optimize the big-data pipelines, data warehouse and data delivery services that are the backbone of FarmTogether’s data-driven farmland investing model.

SR. DATA ENGINEER

Responsibilities
• Work closely with our Head of AI & Automation to build out our big data infrastructure to enable the investment team to identify, price and underwrite farmland.
• Architect, build and launch systems that ingest, sanitize and normalize diverse large-scale datasets into meaningful structured data for analysts, scientists and engineers.
• Collaborate with Data Science Lead to derive features that improve our pricing and underwriting models
• Increase the fidelity and amount of metadata we have about each farm and farmer, as well as the connections between these entities
• Lead data engineering projects to ensure pipelines are reliable, efficient, testable, & maintainable
• Champion a data-driven culture
• Drive a predictable delivery cadence
• Maintain a high-quality, well-documented code base

Minimum Qualifications
• A Bachelor's/Master's degree (or higher) in Computer Science or equivalent work experience required.
• A minimum of 5 years of professional experience building data infrastructure.
• Experience building data pipelines from disparate sources
• Experience building end-to-end data solutions in an agile environment from requirements to production.
• Experience with mpp databases (Redshift, Vertica, etc) or similar big-data technologies (Presto, Spark, Kafa, etc)
• Expertise in relational databases and query authoring (SQL)
• Coding proficiency in Python, Scala or Java
• Strong communication skills; Explaining complex technical concepts to product managers, data analysts, and other engineers shouldn't be a problem for you
• Self-starter that is constantly seeking to improve our data infrastructure
• Resourceful and pragmatic approach to problem solving, not dogmatic. We’re moving fast and breaking things!
• Experience working in a fast-growing startup environment

Preferred Qualifications
• Experience with ML frameworks like Tensorflow, PyTorch, Spark MLlib, XGBoost, and Scikit-Learn
• Familiarity with climate, environmental, pricing and/or geospatial datasets

About Us
The founding and executive teams have decades of institutional experience in ag, farmland, and food investing, having previously deployed over $1B into this asset class. We also have deep financial and tech expertise that allows us to build investment products for the future. We’ve raised several million dollars in VC and angel funding to date, have thousands of investors on our platform, and have deployed millions of dollars into farmland deals across the United States.

Our backers include Blue Seed Collective, Franklin Templeton ($1.5T global asset manager), Richie Prager (a former key executive at BlackRock, the largest asset manager in the world), founders of Grammarly, founder of Pillpack, former CEO of Fonterra (largest dairy exporter in the world) and many other prominent financial, agricultural and tech professionals.

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