Data Engineer

PUIG Deutschland GmbH; Barcelona; Presencial; EUR 65.000 - 90.000; Jornada completa

Descripción de la vacante

Puig is seeking a Data Engineer to design, build and operate enterprise-grade data infrastructure on Google Cloud Platform. You will focus on BigQuery, data quality, governance, observability and security by design to enable analytics and AI across the organization.

You will contribute to shared data capabilities, collaborate with AI engineering teams and help modernize analytics foundations while maintaining robust documentation and data governance practices.

Formación

• 3-6 years of data engineering or analytics engineering experience.
• Hands-on with Google Cloud Platform and BigQuery.
• Experience designing ETL/ELT pipelines and data models.
• Knowledge of data governance, metadata and secure data access.

Responsabilidades

• Design, build and maintain scalable data pipelines on Google Cloud Platform.
• Develop BigQuery data models and curated datasets for analytics and AI.
• Create automated ETL/ELT processes across multiple sources.
• Implement batch, near-real-time and event-driven data flows.
• Collaborate with AI engineering teams to enable ML/GenAI use cases.
• Maintain data workflow documentation and governance practices.

Conocimientos

Data engineering

BigQuery

ETL/ELT

Cloud platforms

Data governance

Herramientas

Google Cloud Platform

BigQuery

Dataflow

Dataproc

Cloud Composer

Cloud Run

Cloud Functions

Pub/Sub

Descripción del empleo

Puig is a major player in the worldwide fashion and beauty industry. We have a wide portfolio of well-known luxury brands across fashion, fragrance, makeup, skincare, and wellness. Founded more than 100 years ago, Puig is a family-owned company with a long-term commitment to our brands and stakeholders.

The Opportunity

Design, build and operate enterprise-grade data infrastructure, reusable data pipelines and governed data assets that enable analytics, AI and business decision-making across the organization.

The role focuses on cloud-native data engineering using Google Cloud Platform, with strong emphasis on BigQuery, data quality, data governance, observability, performance and security by design.

As part of Technology Architecture, the Data Engineer contributes to shared data capabilities that support Data & AI Tech Factory delivery, business data domains, AI engineering and analytics teams across the enterprise.

What you'll get to do

• Contribute to the evolution of the enterprise data platform and data engineering standards.
• Help define reusable patterns for ingestion, transformation, orchestration, monitoring and data productization.
• Support the modernization of analytics and AI data foundations on Google Cloud Platform.
• Promote cloud-first, governed and AI-ready approaches to enterprise data engineering.
• Identify opportunities to reduce duplication and increase reuse across data pipelines, datasets and platform components.

Delivery & Execution

• Design, build and maintain scalable data pipelines and data processing workflows using Google Cloud Platform services.
• Develop BigQuery data models, curated datasets and reusable data layers optimized for analytics and AI consumption.
• Create automated ETL/ELT processes to ingest, clean, enrich and transform data from multiple enterprise and third-party sources.
• Implement batch, near-real-time and event-driven data flows where appropriate, ensuring performance, reliability and operational resilience.
• Support integrations between cloud systems, on-premise systems and third-party applications where data movement or data availability is required.
• Build and optimize data workflows using services such as BigQuery, Cloud Storage, Pub/Sub, Cloud Functions, Cloud Run, Dataflow, Dataproc and Cloud Composer.
• Collaborate with AI Engineering teams to create AI-ready datasets, feature-ready structures and reliable data foundations for ML and GenAI use cases.
• Maintain documentation of data workflows, architectures, data models, dependencies and operational procedures.

Governance & Compliance

• Apply data governance standards for data quality, lineage, metadata, cataloging, documentation and traceability.
• Implement security and privacy controls, including access management, encryption, role-based access and secure data sharing practices.
• Ensure pipelines and datasets comply with internal governance, GDPR and relevant data protection expectations.
• Contribute to observability, monitoring and alerting practices around data pipelines and data platform components.
• Support responsible AI by ensuring that AI-consuming teams rely on trusted, documented, governed and high-quality datasets.

Stakeholder Management

• Collaborate with Miquel Orengo and Technology Architecture stakeholders to align delivery with technical standards and platform priorities.
• Work with Data & AI Tech Factory squads to provide reusable data foundations for domain delivery.
• Partner with Business Data, Consumer Data, Digital Analytics and other data-consuming teams to understand requirements and translate them into scalable technical solutions.
• Coordinate with Integration Engineering when data flows require cross-system connectivity or API-enabled movement.
• Communicate technical constraints and data engineering decisions clearly to both technical and non-technical stakeholders.
• Act as a strong individual contributor within the Data Engineering capability.
• Share engineering standards, patterns and good practices with peers and delivery squads.
• Support code reviews, design reviews and quality gates where requested by the Data & AI Engineering Manager.
• Mentor junior contributors or external partners when appropriate, without formal people-management responsibility.

Contribute to continuous improvement of development standards, release practices and data engineering maturity.

We'd love to meet you if you have

• 3-6 years of experience in data engineering, analytics engineering, cloud data engineering or enterprise data platform roles.
• Proven hands-on experience building scalable data solutions on Google Cloud Platform, especially with BigQuery.
• Experience designing and operating ETL/ELT pipelines, data models, data warehouses or lakehouse-style architectures.
• Experience with data governance, data quality, metadata, lineage or secure data access practices.
• Experience supporting analytics and AI use cases through trusted datasets and production-grade data flows.
• Experience integrating cloud systems with on-premise or third-party data sources is valuable.

We welcome Creators Of All Kinds.

A few things you'll love about us

• An entrepreneurial, creative and welcoming work culture
• A range of learning and development opportunities
• An international company with plenty of opportunities to grow
• A competitive compensation & benefits package

Puig is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status, or any other characteristic protected by law.

At Puig, we are continually looking for enthusiastic and committed individuals from a broad range of backgrounds and experiences to join our team. We believe that creating an inclusive environment in which you feel welcomed, valued, engaged, and empowered strengthens our business and fosters a culture where we are inspired to work hard, challenge ourselves, and be innovative in our thinking. Additionally, we believe that the diversity of our employees makes us a stronger company and better able to serve our customers around the world.