Full Stack Developer

Role Overview

Key Responsibilities

• 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.

• 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.