Systems Engineering Data Analyst

About Zipline

Zipline is the world’s largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products.

Our customers include the world’s largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we’ve built to enable seamless, reliable, global operations.

Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.

We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.

About You and The Role

We are looking for a highly motivated and skilled data analyst to build out system health and performance monitoring within the Systems Engineering team, working closely with the team’s Senior Data Scientist. This role will play a key part in identifying critical fleet issues, improving safety, and removing barriers to Zipline’s growth. The successful candidate will work closely with engineers across Zipline, helping them understand the performance of their systems and how they relate to others, as well as senior leadership, assisting in measuring key company metrics. The ideal candidate has deep experience in data analytics, particularly in monitoring real-world hardware and/or operations, and can work adeptly with both highly technical and non-technical stakeholders to extract actionable insights from complex technical data.

What You’ll Do

• Design and build data analytics solutions, including monitoring dashboards, alerting tools, and ad hoc analyses, to track Zipline’s core flight reliability and safety metrics.

• Collaborate with System Engineers and partner teams to track the health of hardware, software, and operational systems.

• Create software scripts (in SQL and Python) to extract system performance data from raw flight logs.

• Work autonomously with other Data Scientists and Analysts across the company to create and maintain shared data models in our data warehouse, ensuring company-wide access for analytics and reporting.

• Ensure that we are following best practices for efficient data access across multiple technical systems.

• Serve as a source of knowledge and expertise, assisting team members across the company in locating and reporting on their own data.

What You’ll Bring

• 3+ years of experience in data analysis or business intelligence, preferably related to hardware-software systems or operations.

• Strong proficiency in data visualization tools such as Mode, ThoughtSpot, Looker, Tableau, PowerBI, or similar.

• Experience writing SQL queries to extract, manipulate, and aggregate large datasets from relational databases, including complex joins, aggregations, and window functions, with the ability to optimize and debug queries for performance and readability.

• Experience working with Snowflake’s cloud data platform or comparable data warehouse/data lake tools.

• Excellent problem-solving and analytical skills.

• Strong communication skills, with the ability to present complex data in a clear, concise manner to both technical and non-technical audiences.

• Ability to work independently and manage multiple projects simultaneously.

• Inherent self-motivation, adaptability, and creativity.

• Familiarity with Python for data analysis, including working with pandas, numpy, matplotlib, etc., and exploratory analysis in a Jupyter notebook environment.

• Must be willing to relocate to Kigali, Rwanda for this role

Preferred but Not Required:

• Experience using DBT to create data ETL pipelines.

• Experience with GIS and spatial analysis.

• Knowledge of GitHub and the ability to navigate a software pull request workflow.

What Else You Need to Know

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws or our own sensibilities.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!

Please Note

We have received reports stating that certain individuals are reaching out to people under false pretenses, claiming to be Zipline employees, affiliates, agents, or representatives. They may seek to gain access to your personal information or to acquire money from you by offering fictitious employment opportunities or by claiming that they are contacting you on Zipline’s behalf.

Genuine Zipline employees or representatives will never ask you for money or payment in exchange for employment opportunities or other related services. Any such offer of employment or any other service in exchange for fees that claims to be from us is deceitful and part of a fraud.

If you believe you have been targeted by a fraudulent party, we ask that you immediately get in touch with us via email at [email protected] upon receiving a suspicious offer or claim.