Data Engineer

Luzia; Madrid; Presencial; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A leading AI consumer company in Madrid is seeking a Data Engineer to build and maintain scalable data pipelines and architectures that support effective analytics and decision-making. You will collaborate closely with various teams to ensure data quality and reliability. The ideal candidate has over 4 years of experience in data engineering, strong skills in Python and SQL, and proficiency with cloud platforms like AWS and GCP. Join us to innovate and enhance the user experience with AI.

Formación

• 4+ years of experience as a Data Engineer, Analytics Engineer, or similar role.
• Experience with cloud services like AWS, GCP, or Azure.
• Solid understanding of data modeling concepts.

Responsabilidades

• Design, develop, and maintain scalable data pipelines.
• Collaborate closely with product managers and data scientists.
• Monitor, troubleshoot, and improve data pipelines.

Conocimientos

Strong proficiency in Python

Strong proficiency in SQL

Strong communication skills

Experience building data pipelines

Educación

Bachelor's degree in Computer Science or related field

Herramientas

Redshift

BigQuery

Snowflake

AWS

GCP

Azure

Descripción del empleo

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 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).

Data Engineer (Madrid)

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.