Data Engineer

About the Role

Every feature team and business stakeholder at Honeydew relies on the Platform team for data they can trust. As a Data Engineer, you’ll lead the work that makes our data more secure, reliable, and accurate, from hardening our data layer to making data easy for teams to access on their own, to tightening how we protect patient data in a HIPAA environment.

You’ll review and test your teammates’ work and partner with feature teams and other stakeholders to shape what our data platform can do next.

What You'll Build (Your First 6 Months)

• By day 60, monitoring in place for query performance, data quality, and capacity, with the top five issues it surfaces resolved; by day 180, a documented schema change and data quality process that feature teams follow, and no production incidents caused by data layer changes in the areas you support.

• By day 60, at least two data security or governance improvements delivered, such as audit log coverage for PHI access, tighter data store access controls, or automated detection of sensitive data in non-production environments.

How You'll Make an Impact

Design and migrate. You'll work with the engineering manager to identify and plan projects, design data models, and execute migrations using agentic engineering methods.

Build reliable data access. You'll build and maintain data pipelines and reporting access, so feature teams and business stakeholders get data they can trust without filing a request.

Protect and enable. You'll review other engineers' code, especially data-related changes, and help other teams with data requests and security reviews.

What We're Looking For

The Non-Negotiables:

• Data engineering and architecture — production experience designing relational data models, planning and executing data migrations, and building reliable data pipelines, applying current best practices in schema design, query performance, and data quality; experience with data analytics or warehousing.

• Object-oriented programming language — production experience building backend services and APIs.

• Data security and governance — experience securing sensitive data in production, including access control, encryption, audit logging, and handling of PHI or PII, ideally in a regulated environment.

The Nice-to-Haves:

• Experience in a healthcare setting, or another heavily regulated domain.

• Experience with TypeScript, AWS, serverless functions, PostgreSQL, Databricks.

Our Tech Stack

• Languages: TypeScript, Python, SQL

• Backend: Node.js on AWS Lambda, GraphQL (AWS AppSync, Apollo), REST (API Gateway), event-driven architecture (EventBridge, SQS, SNS), authentication (Cognito)

• Data: PostgreSQL (RDS), DynamoDB, OpenSearch, S3

• Analytics: Databricks, dbt, Amplitude

• AI: OpenAI and Anthropic APIs, Cursor