Senior Data Practitioner (Data / Analytics Engineering) - BCN/ MAD/ MUC

AILY LABS; München; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

AILY LABS in Munich is seeking a Senior Data Practitioner to build reliable, scalable data infrastructure powering AI. You'll be responsible for mentoring junior members, optimizing data workflows, and collaborating across teams.

The ideal candidate has strong data engineering skills, a proven track record in building data pipelines, and a startup mindset ready to tackle challenges. This is a hybrid role, requiring 2 days in-office work.

Qualifikationen

• Proven experience in building scalable data infrastructure.
• Excellent understanding of data governance and quality checks.
• Ability to mentor and guide junior data engineers.

Aufgaben

• Build and maintain data infrastructure components.
• Implement data quality frameworks and monitoring systems.
• Collaborate with teams to design data architecture for AI.

Kenntnisse

Data Engineering

Python

Apache Airflow

Data Quality Assurance

API Development

Ausbildung

Relevant Degree in Data Science, Computer Science or related field

Tools

FastAPI

SQLModel

DuckDB

Jobbeschreibung

Senior Data Practitioner

We are looking for Senior Data Practitioners who are passionate about building reliable, scalable data infrastructure that powers AI at scale.

About This Team – Data Practitioners

Data team overview & challenges:

• We are the backbone of Aily’s “Data-to-Decision” engine. We build and own the complete data lifecycle—from ingestion and transformation to quality and delivery. Our team develops robust APIs and scalable infrastructure that ensure high-quality data is always available for the Aily App and our AI models.
• Which data domains and products do we support? We operate at the intersection of business and technology, supporting critical domains including Finance, R&D, GTM (Go-to-Market), M&S (Management & Supply), Spend. Our pipelines power the Aily App across multiple tenants, delivering the insights that drive global enterprises in several industries.
• Key technical challenges:
• Scale: Managing multi‑tenant, config‑driven pipelines that adapt to diverse client needs.
• Reliability: Ensuring 24/7 uptime through automated QA, validations, and proactive monitoring.
• Quality: Implementing sophisticated business logic checks to maintain a “Single Source of Truth.”
• Governance: Orchestrating complex event‑driven and scheduled flows while maintaining strict data security and compliance.
• How do we collaborate? We work as strategic partners with Product, Software Engineering, and ML & Data Scientists.
• Tech Stack: Python (core pipelines, APIs, and CLI tooling), FastAPI and Pydantic for high‑performance REST APIs, dbt for SQL‑based transformation, SQLModel and Alembic for ORM and migrations, DuckDB and DuckLake for embedded analytics, AWS (S3, IAM) for infrastructure, Apache Airflow for orchestration, pytest for QA, GitHub for version control, rigorous PR‑based code review process.

Core Responsibilities

• 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.
• 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.

Who We’re Looking For

• Data Engineers who excel at building reliable, scalable data infrastructure that powers AI decision‑making at enterprise scale.
• Hands‑on builders who love creating robust data pipelines, optimizing systems for performance and cost, and ensuring data quality at every step.
• Strong collaborators who partner with Data Scientists, ML Engineers, Product teams, and business stakeholders to turn raw data into actionable insights.
• Startup mindset: thrives in ambiguity, proactively solves complex data challenges, and improves tooling beyond your immediate scope.
• Ready to Lead Boldly – building the data foundation that enables Aily's AI platform to deliver millions of real‑time insights daily.
• Applicants must have the legal right to work in Spain or Germany.

Location & Details

• Locations: Madrid (MAD), Barcelona (BCN) and Munich
• Contract type: Permanent
• Work policy: hybrid (2 days per week in the office)