Senior Data Engineer
TYB is a community-driven rewards and loyalty platform that connects fans with brands through challenges, feedback, exclusive access, collectibles, and rewards.
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About TYB
TYB operates a platform where fans discover brands, participate in challenges and community experiences, share feedback and product content, earn coins, and receive rewards such as discounts, collectibles, exclusive access, and product drops. For brands, TYB provides community engagement, loyalty and rewards automation, CRM integrations, Shopify integration, customer insights, user-generated content, and tools to increase repeat purchases and lifetime value. Its clients include beauty, health and wellness, retail, and CPG brands.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build and own data infrastructure for analytics, product, and growth decisions. You will develop reliable pipelines, data models, warehouse capabilities, streaming systems, and third-party integrations. You will write backend code, maintain scalable AWS data infrastructure, improve data quality, and help shape architecture and technical standards.
Requirements
- 5+ years of experience as a data engineer or in a hybrid data engineering and backend role
- Strong SQL skills
- Hands-on experience with a cloud data warehouse
- Production experience with dbt
- Experience building and orchestrating pipelines with Airflow or a comparable orchestrator
- Proficiency in Python or TypeScript
- Experience with AWS, RDS/Aurora Postgres, and S3
- Familiarity with Kafka or RabbitMQ
- Cross-functional communication skills
Responsibilities
- Design, build, and maintain ELT/ETL pipelines using Airflow, dbt, and SQL
- Own data warehouse modeling, performance, cost, and data quality
- Build and maintain streaming data pipelines using RabbitMQ or Kafka
- Develop data import and export integrations with third-party platforms and APIs
- Write production backend code in Python or TypeScript for ingestion, transformation, and integrations
- Maintain scalable and cost-efficient AWS data infrastructure using Redshift, RDS/Aurora Postgres, and S3
- Implement testing, monitoring, and documentation practices
- Organize and expose curated datasets for AI and ML features
- Partner with product, engineering, analytics, and business stakeholders on data needs
- Make architecture and tooling decisions as an early data hire
Benefits
- Remote work
- Optional offices in San Francisco
- Flexible time off