Context

Our full data pipeline starts with the crawling and ingestion of massive volumes of social media & physical events data, which are then analyzed by our computer vision models. These predictions mapped to fashion trends and aggregated into time series that feed the metrics and forecasts at the core of our product.

Team

The Data Engineering team owns this entire pipeline: from crawling and ingestion, through transformation and orchestration, to making reliable, well-structured data available to the rest of the company, Data Science, Product, and beyond. We’re responsible for the health, scalability, and evolution of the data stack that everything else at Heuritech is built on.

Our stack is built around Snowflake, dbt, Airflow, Celery, K8s, AWS, and Datadog.

Role

As a Data Engineer, your mission will be to build, maintain, and scale the systems that turn raw crawled data into trustworthy, usable data for the whole company. This includes:

• designing and maintaining Airflow DAGs and orchestration logic

• building and evolving dbt models and transformations in our Snowflake data warehouse

• improving the reliability, monitoring, and data quality of our pipelines

• working on the crawling stack that feeds our pipeline, and its infrastructure

• contributing to internal tools that make data more accessible across teams

• exploring and prototyping new tools or architectures to improve how we orchestrate and process data

You’ll have real ownership over the projects you’re staffed on, with the autonomy to shape the approach and drive improvements as you see fit.

What we’re looking for

You have several years of experience in Data Engineering or Software Engineering with a strong data focus (ideally 3-5+ years). You’re comfortable owning the full lifecycle of a data pipeline from ingestion to orchestration to modeling and you have a good instinct for making data systems robust, observable, and easy to maintain.

You’ve worked with large volumes of data and know how to think about scalability, both on the software and infrastructure side. You’re able to move from prototype to industrialized, production-grade solutions, and you know how to structure, test, and document your code so others can build on it.

Required skills

• Strong proficiency in Python, environments and dependencies tooling such as uv

• Solid SQL skills, data modeling knowledge, and experience with dbt or similar transformation frameworks

• Hands-on experience with workflow orchestration (Airflow or equivalent)

• Experience with a modern cloud data warehouse (Snowflake or equivalent)

• Familiarity with CI/CD practices

• Knowledge of version control with Git

• Comfortable in Linux and/or macOS environments, writing and executing bash scripts

Nice-to-have skills

• Experience with Celery or other task queue systems

• Experience with web crawling / scraping pipelines

• Experience with Kubernetes and containerization (Docker)

• Experience with cloud platform (AWS or equivalent)

• Understanding of agile project management methodologies

• Experience with observability/monitoring tools such as Datadog

• Familiarity with OpenTelemetry or equivalent for observability (traces, metrics, etc.)

• Comfortable leveraging AI tools in your workflow (e.g. Claude), including building custom skills or integrating MCP servers

Soft skills

You take ownership and work autonomously, given a project, you know how to engage with stakeholders, gather the requirements you need, and lead it end-to-end from initial scoping to implementation and communication of the results. We place a lot of value on initiative, we’re looking for someone who naturally spots problems and proposes solutions on their own.

As we’re an international company, you’re comfortable communicating in English, both written and spoken.

• First call to get to know each other and talk about the open position

• Technical test

• Meeting with the Data Engineering team to debrief the technical test and meet your future colleagues

• Meeting with the CTO