Job Description
Role Overview\nWe 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.\n\n### Key Responsibilities\n- Data Engineering (primary focus)\n- Design, build, and operate data pipelines (ETL/ELT) that ingest, transform, and reconcile data across multiple systems and data stores.\n- Own data modeling and schema design, including defining data contracts shared across the platform.\n- Build event-driven data integration flows, ensuring idempotent processing and reliable data delivery between services.\n- Integrate with third-party and legacy systems, handling mismatched data models, partial failures, and reconciliation logic.\n- Monitor, troubleshoot, and optimize data pipeline performance, reliability, and data quality.\n- Collaborate with architects and product teams to define shared data stores, contracts, and access patterns.\n- Instrument pipelines and features for experimentation, measurement, and data-quality monitoring.\n\n### Full-Stack Development (supporting focus)\n- Build and maintain full-stack product features, front-end interfaces and backend/API services, that expose and consume the underlying data.\n- Design and implement RESTful APIs and service-layer components on top of the data platform.\n- Ensure secure, scalable, and maintainable development practices across both data and application layers.\n- Contribute to code reviews, automated testing, release readiness, and production support.\n\n### Required Skills and Experience\n- 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.\n- Strong SQL and data modeling skills, comfortable designing schemas for both operational and analytical use.\n- Hands-on experience with event-driven data integration patterns and idempotent processing.\n- Experience integrating with third-party or legacy systems, including data mapping, transformation, and reconciliation logic.\n- 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).\n- 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.\n- Solid understanding of distributed system reliability and data pipeline observability (monitoring, alerting, data-quality checks).\n- Strong collaboration skills across data, engineering, and product teams.\n\n### Preferred Qualifications\n- Experience with data warehousing or analytics platforms (e.g., Redshift, Snowflake, BigQuery).\n- Experience with workflow orchestration tools (e.g., Airflow, Step Functions).\n- Experience building search, routing, or matching/assignment systems.\n- Experience with CRM or contact-center platform integrations.\n- Experience with AI-assisted or chat-driven product interfaces.\n- Experience instrumenting features or pipelines for A/B testing and experimentation.
