Role Overview
We are looking for a Full Stack Developer — someone who spends the majority of their time designing, building, and operating data pipelines, integrations, and data models, and who also brings solid full-stack development skills to build the APIs and interfaces that expose that data. This is a data engineering-first role with meaningful full-stack exposure, not the other way around.
Key Responsibilities
Data Engineering (primary focus)
- Design, build, and operate data pipelines (ETL/ELT) that ingest, transform, and reconcile data across multiple systems and data stores.
- Own data modeling and schema design, including defining data contracts shared across the platform.
- Build event-driven data integration flows, ensuring idempotent processing and reliable data delivery between services.
- Integrate with third-party and legacy systems, handling mismatched data models, partial failures, and reconciliation logic.
- Monitor, troubleshoot, and optimize data pipeline performance, reliability, and data quality.
- Collaborate with architects and product teams to define shared data stores, contracts, and access patterns.
- Instrument pipelines and features for experimentation, measurement, and data-quality monitoring.
Full-Stack Development (supporting focus)
- Build and maintain full-stack product features, front-end interfaces and backend/API services, that expose and consume the underlying data.
- Design and implement RESTful APIs and service-layer components on top of the data platform.
- Ensure secure, scalable, and maintainable development practices across both data and application layers.
- Contribute to code reviews, automated testing, release readiness, and production support.
Required Skills And Experience
- 4-7 years of professional experience, with the majority of that time spent building data pipelines, ETL/ELT processes, or data integration systems in production.
- Strong SQL and data modeling skills, comfortable designing schemas for both operational and analytical use.
- Hands-on experience with event-driven data integration patterns and idempotent processing.
- Experience integrating with third-party or legacy systems, including data mapping, transformation, and reconciliation logic.
- Working full-stack development skills: backend service development (Node.js, Python, or Java) with RESTful API design, plus front-end development skills (JavaScript/TypeScript, React or an equivalent framework).
- Experience with cloud-native data and application delivery (AWS, Azure, or GCP), including serverless/managed services such as Lambda/Functions, event buses, and managed NoSQL or relational databases.
- Solid understanding of distributed system reliability and data pipeline observability (monitoring, alerting, data-quality checks).
- Strong collaboration skills across data, engineering, and product teams.
Preferred Qualifications
- Experience with data warehousing or analytics platforms (e.g., Redshift, Snowflake, BigQuery).
- Experience with workflow orchestration tools (e.g., Airflow, Step Functions).
- Experience building search, routing, or matching/assignment systems.
- Experience with CRM or contact-center platform integrations.
- Experience with AI-assisted or chat-driven product interfaces.
- Experience instrumenting features or pipelines for A/B testing and experimentation.
