Your mission

Are you ready to take part in the AI revolution in business? If yes, we have an exciting opportunity for you.

We are looking for a Data Engineer passionate about building scalable, reliable data infrastructure that powers AI.

About the team

Our Data team owns the full data lifecycle—from ingestion and transformation to quality and delivery. We build scalable pipelines and APIs that power insights across domains like Finance, R&D, and Go-to-Market.

What you’ll work on

• Designing and maintaining scalable, multi-tenant data pipelines
• Ensuring data quality, reliability, and governance
• Collaborating with Product, Engineering, and Data Science teams

Tech stack

• Languages & Frameworks: Python is our core for pipelines, APIs, and CLI tooling. We use FastAPI and Pydantic to serve typed, high-performance REST APIs to our platform.
• Data Transformation & Modeling: We use dbt for our SQL-based transformation layer and SQLModel with Alembic for ORM-based schema management and versioned migrations.
• Storage & Analytics: We utilize DuckDB and DuckLake as our embedded analytics engine, all hosted on a robust AWS infrastructure (S3, IAM).
• Orchestration & Workflow: Apache Airflow handles our complex event-driven and scheduled job flows.
• Quality & Engineering Excellence: We prioritize reliability through pytest for QA validations, GitHub for version control, and a rigorous PR-based code review process.

Your profile

Mid Data Engineer

• All of the above +
• Design and implement end-to-end data pipelines (ingestion → transformation → quality → delivery) for multiple use cases with growing autonomy.
• Build and maintain data infrastructure components (streaming pipelines, transformations, APIs, catalogs) using modern data tools.
• Implement robust data quality frameworks, monitoring, and alerting systems at scale.
• Optimize data workflows for cost, performance and reliability across multiple datasets.
• Mentor junior team members on data engineering best practices and tooling.

Senior Data Engineer

• All of the above, plus:
• Lead the design and implementation of complex, scalable data platforms and pipelines that support multiple teams and use cases.
• Drive improvements in data infrastructure, tooling and processes that reduce operational burden and improve data team efficiency.
• Own critical data systems end-to-end, from requirements to production monitoring, with only strategic guidance.
• Establish and enforce data engineering standards (quality, governance, reliability, performance) across the organization.
• Collaborate with ML Engineering, Data Science and Product teams to design data architecture that powers AI at scale.
• Principal Data Practitioner – 8+ years of experience

Principal Data Engineer

• All of the above +
• Act as technical authority for the Data Platform, deeply understanding Aily's data architecture and shaping long-term data strategy across teams
• Lead cross-team data architecture discussions and technical design sessions, ensuring scalable, future-proof solutions
• Define and maintain org-wide data standards (quality, governance, reliability, performance, security) and drive adoption across all teams
• Own multiple critical data initiatives simultaneously, managing complexity, external stakeholders, and leadership expectations
• Solve org-critical data challenges and represent data engineering standards as the ultimate quality gatekeeper

What we offer

• Medical insurance
• Holiday flat in Valencia
• Gifts for special occasions
• Anniversary gifts
• Team-building events
• End of the year celebrations
• Day off on your birthday
• Monthly massage day
• Monthly themed lunch
• Community and social initiatives
• Access to Udemy Learning Platform
• German Language Courses
• SAP Courses
• Personal & Professional Growth

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