Senior Analytics Engineer

Zipline•South San Francisco, CA

3d•$140,000 - $175,000

About The Position

Zipline's Application Software team builds the systems that power every part of our business, from the factory floor to real-time delivery operations. We are responsible for the “operating system” of Zipline: critical applications that manage hardware production and inventory, fuel demand generation and customer engagement, enable data-driven decision making, and orchestrate fulfillment, flight, and delivery at scale. Our work spans internal platforms that streamline manufacturing, supply chain, and financial workflows, as well as external-facing applications that allow customers to place and track orders. By connecting every corner of the business through software, we ensure Zipline can operate efficiently, intelligently, and globally. As a Senior Analytics Engineer on our team, you’ll play a key role in unlocking the full potential of data from these systems. You will build and optimize data pipelines, transform raw information to make connections and develop analysis-ready datasets, and serve as a trusted expert for the company’s most important and complex data questions. As a result, Zipline leaders will have high-quality and actionable data to make more informed decisions, innovate faster, and serve our customers better.

Requirements

Bachelor’s degree in a related field, or equivalent industry experience.
7+ years of relevant industry experience.
A strategic mindset, with experience helping define and evolve data strategy, infrastructure, analytics practices, or AI-enabled data workflows.
Fluency with AI tools and a strong instinct for using them to work faster, improve quality, and unlock new ways of answering analytical questions.
Experience building semantic layers, governed metrics, reusable data models, or similar structures that enable both self-serve analytics and AI-assisted data exploration.
Interest in building or improving AI-powered analytics systems, including semantic views, skills, evaluation workflows, and other tools that help users get accurate answers from complex data.
Strong judgment around AI-generated outputs, including knowing when to validate results, inspect source data, question assumptions, and apply human/business context before trusting an answer.
Familiarity with Python or R for statistical analysis, experiment design, or predictive modeling is a plus.
Expertise in writing complex and efficient SQL queries.
Experience with Business Intelligence tools.
Experience with data warehouses, preferably Snowflake.
Experience in schema design and dimensional data modeling, preferably using dbt.
Expertise analyzing large datasets visually to make complex results understandable at a glance.
Excellent analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
Adept at triaging analytics requests and balancing multiple projects, deadlines, and stakeholders.
Excellent communication and interpersonal skills, with the ability to explain complex topics in simple language to diverse audiences.

Responsibilities

Bridge the gap between business problems and the data required to address them.
Become a trusted partner for customer and operational teams, identifying and anticipating analytical needs and delivering high-impact solutions and insights.
Develop and maintain scalable data pipelines to ensure stable, accurate, and reliable data flows seamlessly across systems.
Build semantic views, governed metrics, and reusable data models that make our data easier to understand, trust, and use across both traditional BI tools and AI-powered workflows.
Design, develop, and optimize models to consolidate raw data from multiple platforms and transform it into clean, reusable datasets.
Help improve and extend our internal AI analytics harness, making it increasingly effective at answering data questions accurately, transparently, and in ways that drive real operational impact.
Use AI tools thoughtfully to accelerate your own work, from analysis and documentation to modeling and exploration, while applying strong judgment about where human review, validation, and business context are required.
Partner with engineers to improve data quality at the source and help design software systems that set us up for long-term analytical success. You’ll bring context and insight that actively shape how we build and scale.
Help define our approach to balancing centralized reporting with enabling distributed teams. You’ll build the tools, resources, and data models others need to move quickly and make decisions independently.