Zipline is looking to solve the world’s most urgent and complex access challenges by building, manufacturing and operating the first instant delivery and logistics system that serves all humans equally, wherever they are.
Requirements
- Strong proficiency with Python, SQL, and at least one modern data orchestration tool (Airflow, Prefect, Dagster, etc.).
- Hands-on experience designing data models, ELT/ETL pipelines, and warehouse architectures using Snowflake, BigQuery, Redshift, or equivalent platforms.
- Experience working with distributed systems, APIs, microservices, and event-driven data flows.
- Familiarity with dbt, schema versioning, metadata management, and tested data transformations.
- Experience supporting logistics, supply chain, healthcare, aviation, or robotics systems.
- Background working with government system integrations, compliance reporting, or regulated industries.
- Knowledge of CI/CD workflows, containerization (Docker, Kubernetes), or infrastructure-as-code.
Responsibilities
- Design, build, and maintain robust data pipelines that ingest, clean, transform, and synchronize data across P1 operational systems, internal tools, and external partners’ platforms
- Develop and optimize data models that support analytics, reporting, and machine learning applications across the P1 platform
- Own and evolve Zipline’s P1 data architectureincluding warehouse models, data marts, and integration schemas ensuring maintainability, clarity, and alignment with Zipline’s data standards.
- Collaborate with product, operations, and platform engineers to translate real-world logistics requirements into data solutions that improve service reliability, regulatory reporting, and operational decision-making
- Build and maintain ETL/ELT processes that support order tracking, inventory management, delivery performance, and customer behavior analytics
- Create and manage data infrastructure that scales across geographies, complexity, and evolving business needs
- Build data quality monitoring and alerting frameworks to proactively detect pipeline failures, data drift, schema changes, or anomalous behaviors across geographies.
Other
- 4+ years of experience as a Data Engineer or Backend/Data-focused Software Engineer working on production data systems.
- Clear and thoughtful communication skills, with a strong commitment to documentation and shared ownership.
- Comfort collaborating with cross-functional partners from engineering, operations, regulatory teams, and commercial teams.
- Clear, concise communication skills and ability to translate technical concepts for non-technical stakeholders.
- Strong problem-solving skills and attention to detail.
