Title: Sr. Data & Full-Stack Engineer

Location: 100% remote; will need to work EST Hours

Duration:12-month contract

Manager Notes:

Team / Project Overview

• This is a new project that is about to launch, focused heavily on the IAM/identity space.
• The team is working on an Agentic AI initiative where new agents will be deployed to identify and assess risk.
• The project involves building a new application/system from the ground up.
• The team is currently very small: 2 FTEs. This hire will become the 3rd resource
• Because of the team size and greenfield nature of the project, this person will have significant ownership and influence over the technical solution.

This is probably the most important piece to emphasize:

70% – API / GraphQL / Application Development

30% – Data Engineering / Pipelines

So, although the title may be Data Engineer, they would not primarily target traditional Data Engineers who spend 80–90% of their time building ETL pipelines.

Looking for someone who can build the API/application layer and also understands the underlying data engineering architecture.

Primary Responsibilities

• The role is essentially a Senior Data Engineer / Full Stack Engineer with a heavy API/GraphQL focus.
• Build a GraphQL API from the ground up.
• Design and develop low-latency APIs that will ultimately be consumed by employees across the client.
• The API will become part of a critical runtime/developer workflow, so performance, reliability, scalability, and monitoring are extremely important.
• Build and enhance data pipelines that feed the API.
• Bring data from multiple sources together and make it available through the API.
• Extend existing data pipelines while building new pipeline capabilities.
• Develop integrations between data platforms and application/API layers.
• Establish strong monitoring and observability around the application and APIs.
• Work closely with the other two engineers to design and build the new platform.
• AWS / Data Technologies

Must-Have Skills

• Strong API development experience.
• Strong GraphQL experience — ideally someone who has actually built GraphQL APIs rather than simply consumed them.
• Experience building low-latency APIs/services.
• Strong AWS experience.
• Strong data engineering fundamentals.
• Experience building data pipelines.
• Experience with technologies such as Spark/PySpark, Glue, Snowflake, or comparable platforms.
• Strong understanding of how data moves from source → pipeline → storage → API/application.
• Strong monitoring/observability experience.

Nice to Have

• IAM / identity/security domain experience.
• Experience with Agentic AI / AI applications.
• Experience building greenfield applications.
• DynamoDB experience.
• PostgreSQL experience.
• Lambda/serverless experience.
• Experience supporting high-traffic or business-critical APIs.