Company Description Blyze Labs specialises in data analytics and engineering for e-commerce and retail brands, with a focus on high-growth DTC companies. The team helps 8–9-figure brands uncover wasted ad spend, increase customer retention, and automate reporting to enable data-driven decision-making. We're a small team. You'll work closely with clients and have real ownership over the work.

Role Description The Analytics Engineer will design, build, and maintain data pipelines, data models and dashboards that power analytics for e-commerce and retail clients. Day-to-day, you'll be:

Building and maintaining dbt data models in SQL across client stacks (BigQuery, Snowflake)

Delivering dashboards in Looker, Omni, Excel or similar tools.

Running ad hoc analyses and answering business questions with data.

Maintaining and troubleshooting data pipelines. Building lightweight internal tools using AI; we use Claude heavily and expect this to be a core part of how you work, not an experiment

Owning data quality, documentation, and pipeline reliability across client projects What we're looking for

High agency: you figure things out, flag blockers early, and don't wait to be told what to do.





Eagerness to learn: the stack evolves, clients change, and the best work here comes from people who are genuinely curious and pick things up fast.

You've built something: a data product, a tool, a side project. Something that was yours.

Clear written and spoken English: you'll communicate directly with English-speaking clients.

Experience using SQL: you can write and debug complex queries.

Hands-on dbt experience: models, tests, documentation, incremental strategies.

Mid-Senior or Junior profiles. Nice to have:

Experience in Data Modelling and Data Warehousing.

Hands-on dbt experience — models, tests, documentation, incremental strategies.

Solid Data

Analytics skills to validate data, support reporting, and enable actionable insights.

Familiarity with modern data stacks and cloud-based data platforms (e.g., Snowflake, BigQuery, Redshift, dbt, Airflow).

Background in Computer Science, Data Science, Engineering, Mathematics, or a related field.

Experience with e-commerce, retail analytics or marketing performance data.

📌 Analytics Engineer (Argentina)
🏢 The Analytics Network
📍 Argentina