Full-Stack Software Engineer, Platform Data

Zanskar•Salt Lake City, UT

1d•Hybrid

About The Position

The Platform Data team at Zanskar is responsible for organizing all of the company's data, including internal, purchased, and public sources, and transforming it into actionable insights. This involves building data systems and pipelines to consolidate messy, heterogeneous data into a trustworthy central repository, as well as developing web applications that present this data to users. The goal is to make geothermal energy a cheap and vital contributor to a carbon-free electrical grid by enabling geothermal experts to make decisions with confidence through a scalable data ecosystem. This role offers the opportunity to have a direct impact on displacing carbon emissions and provides growth opportunities within a startup environment. The successful candidate will design and operate data pipelines, reconcile data from various sources, and build web applications such as dashboards and internal tools. They will own features end-to-end, from system architecture and pipeline design to API and frontend development, ensuring the smooth operation of the entire system. Collaboration with cross-functional teams to understand data needs and translate them into functional products is key.

Requirements

Proven experience as a full-stack builder, having designed and maintained backend data systems and associated user-facing applications.
Fluency in Python and SQL for backend development.
Fluency in TypeScript and React for frontend development.
Experience owning features that span from data source to user interface.
Experience designing schemas and building reliable data pipelines for transforming messy data into clean, queryable forms.
Understanding of idempotency, data quality, and handling upstream source changes.
Comfort deploying and operating systems on a public cloud (AWS or GCP).
Experience with containers (Kubernetes).
Experience with infrastructure-as-code tools (e.g., Pulumi and Terraform).
Ability to research options, make recommendations, and perform best work under challenging constraints.
Proficiency in leveraging and delegating to AI tools as a core part of the workflow.

Nice To Haves

Experience with orchestration and warehouse tooling (e.g., Airflow, Dagster, dbt, Snowflake, or BigQuery).
Experience with geospatial or scientific data, including raster/vector formats, large file stores, PostGIS, or similar.

Responsibilities

Design and operate pipelines that ingest data from internal systems, purchased datasets, and external feeds.
Reconcile and model data into clean, trustworthy, and findable formats.
Build web applications, including dashboards, internal applications, and other interfaces, to deliver data to stakeholders.
Own features end-to-end, including system architecture, pipelines, APIs, and frontends.
Ensure the entire data system runs smoothly and reliably.
Partner with teams across the organization to understand their data needs and build solutions.
Deploy and operate built systems on a public cloud (AWS or GCP) using containers (Kubernetes) and infrastructure-as-code (e.g., Pulumi and Terraform).