Data Engineer

About Us:

Luzia is Europe's fastest-growing AI consumer company, redefining conversational AI with cutting-edge large language models and an unparalleled user experience. With a strong and rapidly expanding presence in Brasil, we're on a mission to make Luzia the go-to AI personal assistant, empowering millions of users to simplify and enhance their everyday lives.

At Luzia, we ship fast: keep it simple, learn from every experiment, own outcomes, and and build what our users need. We thrive in a fast-paced environment and expect everyone to use AI daily—automating the routine and amplifying creativity—because using AI isn't optional; it's how we win.

Hypergrowth startup with 80M+ users worldwide in under 3 years.

 Latin America as a core market with more than 60% of our user base.

 Backed by top-tier investors (Khosla Ventures, Prosus Ventures, A-Star, Monashees  and more) .

As a Data Engineer, you'll join our engineering team in Madrid, building and operating the data pipelines and models that power analytics, decision-making, and AI-driven product features. You'll work at the intersection of product, engineering, and data, helping ensure that data across the company is reliable, scalable, and easy to use.

Responsibilities:

• Data Pipelines & Architecture: Design, develop, and maintain scalable data pipelines and data architectures supporting analytics, experimentation, and machine-learning use cases.

• LLM-Enabled Data Workflows: Work on data workflows that leverage LLMs in production, such as classification or analysis of user inputs.

• Transformation Layer: Build and maintain the transformation layer (ELT), developing SQL models tailored to different use cases and audiences.

• Data Quality & Reliability: Implement best practices to ensure data quality, consistency, and security across data workflows.

• Cross-Functional Collaboration: Collaborate closely with product managers, software engineers, analysts, and data scientists to understand data needs and deliver effective technical solutions.

• Operational Excellence: Monitor, troubleshoot, and improve data pipelines to ensure reliability and performance.

• Stack Evolution: Contribute to the continuous improvement of the data stack, adopting new tools and practices as the business and data needs evolve.

Requirements:

• Experience: 4+ years of experience as a Data Engineer, Analytics Engineer, or in a similar role.

• Core Skills: Strong proficiency in Python and SQL.

• Data Warehousing: Experience working with modern data warehouses (e.g. Redshift, BigQuery, Snowflake).

• Cloud Platforms: Hands-on experience with cloud services (AWS, GCP, or Azure).

• Data Pipelines: Experience building, deploying, and maintaining data pipelines end-to-end.

• Data Modeling: Solid understanding of data modeling concepts such as dimensional modeling and slowly changing dimensions.

• Communication: Strong communication skills and fluency in English; comfortable working in an English-speaking environment.

• Product Awareness: A product-minded approach to data, ensuring data solutions support real business and user needs.

• Education: Bachelor's degree in Computer Science, Engineering, or a related field.

Nice-to-Haves:

• Experience with the AWS data stack (e.g. Redshift, Glue, Spectrum).

• Familiarity with Infrastructure as Code practices (e.g. Terraform).

• Experience with data orchestration tools such as Airflow or Prefect.

• Experience with data transformation frameworks like dbt or SQLMesh.

• Exposure to machine learning workflows or LLM-powered data use cases.

• Experience working with large-scale B2C datasets.