Senior Data Engineer

Data Engineer

Fully remote. US-based preferred. If international, significant overlap with US working hours is required.

TYB is an AI-powered community commerce platform connecting brands with their most passionate fans through challenges, rewards, and social features. We're Series A and moving fast across a dual-sided marketplace that serves both consumers and brand partners.

We're hiring a Data Engineer to build and own the data infrastructure that powers TYB's analytics, product, and growth decisions. You'll work at the intersection of data engineering and backend development: most of your time will go toward pipelines, warehousing, and data modeling, but you'll also build and maintain the integrations that move data in and out of TYB.

This is a foundational hire on the data side. You'll have real ownership over how data flows through the company, a lot of autonomy in a 0-1 environment where process is still being built, and direct influence over the architecture decisions that the rest of the team builds on top of.

We build with AI, and we expect you to as well — using AI to move faster in your own workflow (spec writing, debugging, pipeline design, documentation) and thinking about where automation and AI-assisted tooling can reduce manual data work across the org.

Responsibilities:

• Design, build, and maintain reliable ELT/ETL pipelines using Airflow, dbt, and SQL
• Own our data warehouse — modeling, performance, cost, and data quality
• Build and maintain streaming data pipelines (RabbitMQ / Kafka) for real-time and near-real-time use cases
• Develop integrations for data import and export with third-party platforms (e.g., Shopify, Braze, and other partner or vendor APIs)
• Write production backend code in Python and/or TypeScript to support data ingestion, transformation, and integration work
• Work across our AWS environment, including Redshift, RDS/Aurora (Postgres) and S3, to keep data infrastructure scalable and cost-efficient
• Implement testing, monitoring, and documentation practices so data is trustworthy and issues surface early
• Organize and expose curated datasets to support AI and ML features across the product, in close collaboration with the teams building on top of them
• Partner with product, engineering, analytics and business stakeholders to understand data needs and translate them into pipelines and models
• Make architecture and tooling decisions as an early data hire, with room to shape standards as the team grows

Requirements:

• 5+ years of experience as a data engineer, or in a hybrid data engineering / backend role
• Strong SQL skills and hands-on experience with a cloud data warehouse (Redshift or equivalent, e.g., Snowflake, Databricks, BigQuery)
• Production experience with dbt for data modeling and transformation
• Experience building and orchestrating pipelines with Airflow (or a comparable orchestrator)
• Proficiency in Python or TypeScript for backend and integration work
• Experience with AWS, including RDS/Aurora (Postgres) and S3
• Familiarity with streaming/message systems such as Kafka or RabbitMQ
• Comfortable in a 0-1 environment: scrappy, self-sufficient, and able to make sound calls without a fully built-out data team around you
• Strong communicator who can work cross-functionally with product, engineering, analytics, and business stakeholders
• Experience building integrations with e-commerce or marketing platforms (Shopify, Braze, Klaviyo, or similar)
• Experience with CDC or zero-ETL ingestion patterns
• Experience with feature stores or similar tooling for serving data to ML/AI applications
• Early-stage startup experience
• Experience mentoring or setting technical direction for other data/backend engineers

What We Offer:

• Remote work, with optional offices in San Francisco
• Competitive salary
• Flexible time off
• Work environment where you can be involved in shaping the product early on, own its development end-to-end, with freedom and flexibility to figure things out as you go