Data Lead Engineer (Ibiza)

As a Senior Data Lead Engineer you will drive the evolution of our cloud-based Data, AI, and BI platforms.You will play a key technical leadership role, shaping our lakehouse architecture, enabling AI/ML use cases, and guiding engineering best practices across teams.ResponsibilitiesLead the Data, AI & BI roadmap for GTB, ensuring scalability, resilience, security, and cost efficiency.Design and evolve our data lakehouse architecture.Define and build domain-oriented data products aligned with data mesh principles (data-as-a-product, SLAs, contracts, domain ownership).Build and maintain data ingestion, ETL and transformation pipelines including CDC-based and event-driven ingestion.Implement and enforce data governance, data rules, data quality, data normalization/cleaning and guardrails.Enable AI/ML and LLM use cases (training, feature engineering, RAG, fine-tuning, guardrails, monitoring).Qualifications5+ years in Data Engineering, Data Platforms, AI Engineering or Advanced Analytics, ideally in large or regulated environments.Proven experience designing and building cloud data platforms and data lakehouse architectures (preferably AWS).AWS experience: S3, Lake Formation, Glue (Jobs, Crawlers, Data Wrangler), EMR.Hands-on experience with Databricks or EMR for large-scale data transformation.Strong background in data ingestion and ETL.Experience with CDC pipelines and event-driven architectures for ingesting operational/transactional data.Experience integrating on-premise data lakes with cloud platforms in hybrid architectures.Experience enabling AI/ML solutions in production environments.xqysrnhInvolvement in data governance, data quality, data rules and guardrails.#J-*****-Ljbffr

Build and maintain data ingestion, ETL and transformation pipelines including CDC-based and event-driven ingestion.Implement and enforce data governance, data rules, data quality, data normalization/cleaning and guardrails.Enable AI/ML and LLM use cases (training, feature engineering, RAG, fine-tuning, guardrails, monitoring). Qualifications5+ years in Data Engineering, Data Platforms, AI Engineering or Advanced Analytics, ideally in large or regulated environments.Proven experience designing and building cloud data platforms and data lakehouse architectures (preferably AWS). AWS experience: S3, Lake Formation, Glue (Jobs, Crawlers, Data Wrangler), EMR.Hands-on experience with Databricks or EMR for large-scale data transformation.Strong background in data ingestion and ETL.Experience with CDC pipelines and event-driven architectures for ingesting operational/transactional data.Experience integrating on-premise data lakes with cloud platforms in hybrid architectures.Experience enabling AI/ML solutions in production environments. xqysrnhInvolvement in data governance, data quality, data rules and guardrails. #J-*****-Ljbffr