Data Engineer

Ubique Systems; Spain (TX); Hybrid; USD 70,000 - 94,000; Full time

Job summary

A leading technology company is seeking a Technical Expert - Data & AI to provide technical leadership in designing, building, and operating enterprise-grade data and AI platforms. This role requires expertise in cloud technologies and a strong background in managing data solutions. Ideal candidates should have over 5 years in data and AI, with a proven track record in deploying models and mentoring teams. The position is hybrid, based in Malaga, Spain, offering a dynamic work environment.

Qualifications

• 5–8+ years in data, AI, cloud, or data engineering.
• 3+ years designing enterprise data / AI architectures.
• Proven experience deploying ML / AI models to production.

Responsibilities

• Define standards, architectures, and best practices for data & AI platforms.
• Design and support data pipelines, data lakes/warehouses.
• Lead and support ML/AI model deployment using MLOps best practices.
• Design and validate LLM‑based solutions.
• Evaluate tools and technologies; lead PoCs and benchmarking.
• Ensure governance, security, compliance, and data quality across platforms.
• Act as a technical reference and mentor for data engineers and data scientists.
• Collaborate with business and compliance teams.
• Document architectures and technical standards.

Skills

Python

SQL

AWS

Azure

GCP

Spark

Databricks

Kafka

Airflow

Trino

Docker

Kubernetes

RAG architectures

MLOps

Job description

Job Title : Technical Expert - Data & AI

Location : Malaga, Spain - Hybrid : 3-4 Days to Office Every Week

Duration : Permanent

Employment Type : Full-Time

Roles & Responsibilities

We are looking for a Technical Expert – Data & AI to provide technical leadership and deep expertise in designing, building, and operating enterprise‑grade data and AI platforms. This role acts as a key technical reference within the CIO organization, ensuring scalable, secure, and well‑governed data and AI solutions.

Key Responsibilities

• Define standards, architectures, and best practices for data & AI platforms (cloud, on‑prem, hybrid)
• Design and support data pipelines, data lakes/warehouses, streaming, and analytics platforms
• Lead and support ML/AI model deployment using MLOps best practices (monitoring, versioning, reliability)
• Design and validate LLM‑based solutions, including RAG architectures, embeddings, and semantic pipelines
• Evaluate tools and technologies; lead PoCs and benchmarking
• Ensure governance, security, compliance, and data quality across platforms
• Act as a technical reference and mentor for data engineers, data scientists, and architects
• Collaborate with business, security, infrastructure, and compliance teams
• Document architectures, decisions, and technical standards

Required Technical Skills

• Languages: Python, SQL (Scala / Java / R a plus)
• Data & Cloud: AWS / Azure / GCP, Spark, Databricks, Kafka, Airflow, Trino
• Data Modeling: Relational, dimensional, NoSQL, data lakes & warehouses
• ML / AI / MLOps: Model training & inference, CI / CD, Docker, Kubernetes, monitoring
• LLMs & GenAI: RAG architectures, embeddings, model selection, evaluation, safety & hardening
• Infrastructure: IaC, automation, CI / CD pipelines
• Security & Governance: Data protection, access control, compliance standards

Experience

• 5–8+ years in data, AI, cloud, or data engineering
• 3+ years designing enterprise data / AI architectures
• Proven experience deploying ML / AI models to production