Role Summary

As a Senior Data Lead Engineer , you will lead the evolution of cloud-based data, AI, and BI platforms, owning the data lakehouse architecture and enabling high-impact analytics and AI use cases in a regulated, large-scale environment.

What You’ll Actually Do

- Own and evolve the data & AI roadmap ensuring scalability, security, and cost efficiency.
- Design and maintain the enterprise lakehouse architecture.
- Deliver high-quality, trusted datasets for analytics, BI, and AI use cases.
- Act as a technical leader and mentor within the data organization.

Must-Have Requirements (Real Essentials)

These are the non-negotiables—everything else is a plus.

Core Experience

- 5+ years in Data Engineering / Data Platforms / Advanced Analytics (enterprise or regulated environments).
- Proven experience designing and owning cloud data platforms and lakehouse architectures (preferably AWS).
- Hands‑on experience with Databricks or EMR (Spark) for large‑scale data processing.
- Strong background building data ingestion & ETL pipelines, including CDC and event‑driven architectures.
- Experience enabling AI/ML use cases in production (end‑to‑end, not just POCs).

Architecture & Engineering

- Strong knowledge of AWS data services (S3, Glue, EMR, Lake Formation).




- Solid SQL and Python for data processing and automation.
- Experience with hybrid architectures (on‑prem + cloud) and enterprise data integration.
- Practical understanding of data governance, data quality, lineage, and security guardrails.

Data as a Product

- Experience working with business and BI teams to define KPIs and deliver consumable datasets.
- Ability to design well‑modeled datasets and semantic layers optimized for analytics and reporting.
- Familiarity with data mesh principles (domain ownership, data‑as‑product mindset).

Leadership

- Proven ability to lead technically, mentor engineers, and influence stakeholders without direct authority.
- Strong communication skills with both technical and non-technical audiences.

Nice to Have (We Won’t Filter You Out for This)

- AWS or Databricks certifications.
- Experience with ML workflows (feature engineering, training, deployment, monitoring).
- Exposure to LLMs (RAG, fine‑tuning, prompt engineering, guardrails).
- Experience with CI/CD, orchestration tools, or Infrastructure as Code.
- Familiarity with BI tools (QuickSight, Power BI, Qlik) from a data provider perspective.
- 100 % Remoto

📌 Senior Data Lead Engineer (Colombia)
🏢 UST España & Latam
📍 Colombia