UST is seeking a Senior Data Lead Engineer to drive the evolution of data, AI, and BI platforms on the cloud. The role involves leading the data, AI, and BI strategy and roadmap, designing and evolving data lakehouse architecture, and developing and maintaining data ingestion, ETL, and transformation pipelines.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Role Description
We are still looking for talent… and we would love for you to join our team!
For over 25 years, UST has worked alongside the world’s best companies to make a real impact through business transformation. Driven by technology, inspired by people, and guided by our purpose, UST supports clients from design to implementation. Together, with more than 30,000 employees in 30 countries, we build to create limitless impact, reaching billions of lives in the process.
We are looking for a Senior Data Lead Engineer, you will drive the evolution of our data, AI and BI platforms on the cloud.
Note: this role requires relocation to Málaga, Spain.
While the relocation process is completed, the selected candidate will work remotely on Spanish working hours (CET). Once in Málaga, the position will transition to a hybrid model (onsite + remote).
However, there is also the possibility to perform this role remotely from Colombia, also following Spanish working hours (CET). We are open to both modalities depending on the selected profile.
What You’ll Do
- Lead the Data, AI & BI strategy and roadmap.
- Design and evolve our data lakehouse architecture.
- Build domain-oriented data products following data mesh principles.
- Develop and maintain data ingestion, ETL and transformation pipelines (CDC + event-driven).
- Integrate cloud platforms with our SCIB on‑premise data lake, ensuring governance and lineage.
- Implement strong data governance, quality rules and guardrails.
- Deliver high‑quality datasets and semantic layers for BI, KPIs and reporting.
- Enable AI/ML and LLM use cases (training, RAG, fine‑tuning, monitoring).
- Promote engineering best practices and mentor data/ML/BI engineers.
- Collaborate with GTB & SCIB stakeholders to deliver high‑impact data and AI initiatives.
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- 5+ years in Data Engineering, Data Platforms, AI Engineering or Advanced Analytics.
- Experience designing cloud data platforms & lakehouse architectures (preferably AWS).
- Hands-on with Databricks or EMR for large‑scale transformations.
- Strong ETL/ingestion background (CDC, event-driven).
- Hybrid architectures (on‑prem + cloud).
- Production-grade AI/ML enablement.
- Data governance, lineage, rules, guardrails.
- Collaboration with BI teams on KPIs and data modelling.
- English advanced (B2+)
- Bachelor’s degree (or higher) in Computer Science, Engineering, Math, or related.
- Additional training in Data Engineering / AI / Analytics is a plus.
Cloud & Data: AWS (S3, Lake Formation, Glue, EMR), Parquet, Delta/Iceberg, multi‑zone lakehouse design.
Engineering: Spark (PySpark/Scala), SQL, Python, ETL, orchestration, observability, data quality.
AI/ML: Feature engineering, training/validation, deployment, monitoring, MLflow, SageMaker.
LLMs: Prompt engineering, fine‑tuning, RAG, evaluation, Bedrock/Quick Suite.
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Governance: Access control, masking, anonymisation, data rules, CDAIO alignment.
Soft Skills
- Excellent communication with technical & non‑technical stakeholders.
- Leadership and mentoring experience.
- Proactive, hands-on, outcome-oriented.
- Adaptability in complex, global, regulated environments.
- Team-focused and collaborative.
- AWS certifications (Data Analytics, ML, Solutions Architect).
- Databricks certifications.
- CI/CD for data/ML pipelines.
- IaC for data & AI platforms.
- Experience with BI tools (QuickSight, Power BI, Qlik).
- Agile (JIRA, Confluence).
Skills
data engineering,etl,data lakehouse architecture,ai,AWS
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