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Trigo is Crafting Tomorrow's Retail Experience
We started with a simple question: How can vision AI make shopping better for everyone? Today, our team of passionate experts is transforming how people shop and how retailers operate, one store at a time.
Our goal is to solve real retail challenges by developing advanced computer vision AI that prevents loss, enables grab-and-go shopping, and turns store data into valuable insights, all while delivering clear value from day one.
With multiple global deployments, deep partnerships with leading retailers, and a product suite that’s proving its impact every day, Trigo isn’t just imagining the future of retail, we’re building it.
We are looking for an experienced Data Engineer to own and evolve Trigo’s data infrastructure and analytics platform.
You will design and build scalable data pipelines and data models, working with large and diverse datasets generated across Trigo’s global retail deployments. You will own the data lifecycle from ingestion and transformation through orchestration, reliability, and analytics-ready datasets.
As a key technical owner of Trigo’s data platform, you will also work closely with analysts, Product, R&D, Operations, and Customer Success to build trusted data products, evolve our BI semantic layer, and turn complex data into scalable solutions
A day in the life
Design, build, and maintain scalable ETL/ELT pipelines processing large and diverse datasets.
Own and evolve Trigo’s data architecture, from ingestion and transformation through analytics-ready data models and consumption.
Build reliable data workflows and orchestration processes, with a focus on scalability, performance, and maintainability.
Design and maintain curated data models that power analytics, operational workflows, and data-driven products.
Ensure data quality, observability, monitoring, and reliability across datasets and pipelines.
Develop and evolve the BI semantic layer, enabling trusted metrics and self-service analytics across the company.
Work closely with R&D and Product on data integrations and new data-driven capabilities, including use cases that bridge offline analytics and production systems.
Partner with analysts and business stakeholders to translate complex requirements into scalable data solutions.
You bring to the table
4+ years of experience as a Data Engineer, Analytics Engineer, or similar hands-on data role
Strong command of SQL and proficiency in Python for data modeling and transformation
Experience with modern data tools such as dbt, BigQuery, and Airflow (or similar)
Proven ability to design clean, scalable, and analytics-ready data models
Familiarity with BI modeling and metric standardization concepts
Experience partnering with analysts and stakeholders to deliver practical data solutions
A pragmatic, problem-solving mindset and ownership of data quality and reliability
Excellent communication skills and ability to connect technical work with business impact