Data Architect (Snowflake Expert)

Keysight Technologies; Madrid; Presencial; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

A leading technology firm in Madrid is seeking a Senior Applied Data Scientist to join their AI Labs team. The ideal candidate will have a Master’s degree and over 5 years of experience in data science. Responsibilities include developing scalable data architectures, maintaining ETL pipelines, and collaborating with experts to derive insights from data. This position offers the opportunity to shape innovation in advanced technology fields such as 5G and quantum systems.

Formación

• Master’s degree in Data Science, Statistics, Computer Science, or related field.
• 5+ years of experience as an applied data scientist.
• Expert proficiency in Python and SQL.

Responsabilidades

• Partner with experts to identify data sources and define ML-relevant features.
• Architect data lakes for efficient data access.
• Clean and integrate data from various sources.
• Develop ETL pipelines using SQL and Python.

Conocimientos

Python

SQL

Statistics

Data manipulation libraries

Machine Learning workflows

Relational and NoSQL databases

Big data tools (Spark, Kafka)

Cloud platforms (Azure/AWS/GCP)

Educación

Master’s in Data Science, Statistics, or related field

Herramientas

Python

SQL

Snowflake

Spark

Docker

Kubernetes

Power BI

Tableau

Descripción del empleo

About Keysight AI Labs

Keysight's AI Labs is a global R&D group pioneering the integration of AI throughout Keysight’s test, measurement, and design solutions. Our mission is to transform how engineers design, simulate, and validate advanced systems—from 6G and semiconductors to quantum and automotive—by embedding AI throughout our workflows.

Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. With ~15,000 employees, we create world‑class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries.

Job Summary

As part of this growing team, you will join a vibrant, cross‑functional environment that brings together experts in ML engineering, data science, physics‑informed modeling, and software development. You’ll work closely with domain experts across RF, EM, circuit design, and test & measurement to accelerate scientific innovation through AI.

Position

Senior Applied Data Scientist

Key Responsibilities

• Partner with internal experts to identify critical data sources and define ML‑relevant features
• Architect and build scalable data lakes / databases for standardized and efficient cross‑org data access
• Clean, align, normalize, and integrate data from simulations, measurements, and operational systems
• Develop and maintain reproducible ETL / ELT pipelines for structured and unstructured data using SQL, Python, Snowflake, and cloud‑native workflows
• Perform EDA, feature engineering, regression, and dimensionality reduction to generate high‑value insights
• Ensure data governance, lineage, metadata management, and compliance
• Support experiment design, hypothesis testing, and statistical modeling
• Work closely with ML engineers to accelerate model training, deployment, and ongoing monitoring

Qualifications

• Master’s in Data Science, Statistics, Computer Science, Electrical Engineering, or related quantitative field
• ~5+ years of experience as an applied data scientist or hybrid DS/DE role
• Expert proficiency in Python, SQL, and data manipulation libraries
• Strong background in statistics, algorithms, and data structures
• Experience with relational and NoSQL databases and designing scalable data architectures
• Hands‑on experience with big data tools (Spark, Kafka, Snowflake, Databricks, Hadoop)
• Experience supporting ML workflows — MLOps, CI/CD, containerization (Docker/Kubernetes)
• Experience with cloud platforms: Azure / AWS / GCP
• Clear track record of driving data‑to‑value outcomes in wireless, electronics, semiconductor domains
• Familiarity with deep learning frameworks and ML for time‑series or unstructured data
• Experience with Power BI, Tableau, Plotly
• Knowledge of data governance, lineage, metadata management tools