We are looking for an experienced Data Engineer to own and evolve data infrastructure and analytics platform.
You will design and build scalable data pipelines and data models, working with large and diverse datasets generated across Trigos 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 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 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.
Requirements: 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
This position is open to all candidates.