Sr. Full-Stack Engineer, Data Systems

Datavations•New York, NY

3d•$150,000 - $170,000•Remote

About The Position

Datavations is a leading New York-based data and AI software company specializing in the $2.3 trillion dollar building materials industry. Datavations provides manufacturers with real-time, store-level visibility into pricing, assortment, and inventory across major retailers. This role focuses on owning the product taxonomy and attributes domain end-to-end, including the data systems that organize the market and the applications that enable interaction with them. It's a hands-on role with significant architectural latitude for someone seeking full ownership of a critical system. The role involves owning the attribute extraction engine (LLM-based at production scale), the transformation layer using dbt models, orchestration and reliability for data pipelines (Dagster), and the associated internal and customer-facing applications (React/Next.js). It also includes managing the write path for data changes, ensuring data quality and observability, and establishing engineering standards for the domain. A significant part of the platform utilizes AI, including an LLM extraction engine, a rules engine, and an in-app assistant. The focus is on building AI systems properly, with an emphasis on evaluation, versioning of prompts and rules, tool-calling, and considering cost and latency as design constraints.

Requirements

At least 5 years of experience in Cloud Infrastructure, Site Reliability Engineering (SRE), or Platform Engineering.
Strong expertise with Terraform and infrastructure as code (IaC).
Experience with CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI/CD, ArgoCD).
Strong expertise in architecting solutions using AWS services.
Experience in Python, SQL, dbt, and modern orchestration tools (e.g., Dagster, Airflow, Prefect).
Proficiency with a columnar warehouse (e.g., ClickHouse, Snowflake, BigQuery).
Experience with full-stack development (TypeScript, Next.js or similar).
Experience building production data pipelines and maintaining observability/reliability.
Experience with AI/LLM-based systems, including evaluation and versioning of prompts.
Experience with data visualization tools (e.g., Tableau, Power BI) and project management tools (e.g., Jira).

Nice To Haves

Retail, e-commerce, or point-of-sale data experience.

Responsibilities

Own the attribute extraction engine, including its LLM-based extraction at production scale, configuration model, quality gates, and cost profile.
Manage the transformation layer for the product taxonomy and attributes domain, including dbt models for standardization and an override model for human judgment.
Ensure orchestration and reliability for data pipelines using Dagster, including monitoring, retries, alerting, and recovery tooling.
Own the internal and customer-facing applications, including the React/Next.js front end, backend services and APIs, application architecture, deployment, and CI/CD.
Manage the write path for data changes, ensuring validation, logging, and visibility before shipping.
Implement and maintain data quality and observability, including automated testing and statistical detection of issues.
Establish and enforce engineering standards for the domain, including documentation, tests, runbooks, and review culture.
Build and manage AI/LLM-based systems, focusing on evaluation, prompt/rule versioning, tool-calling, and cost/latency optimization.