Senior Data Engineer | Spark Expert

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

Descripción de la vacante

A leading technology firm in Madrid is searching for a Senior Applied Data Scientist. This role involves partnering with experts to architect scalable data systems, manage data from various sources, and enhance machine learning workflows. The ideal candidate should possess a Master's degree and 5+ years of experience in data science, especially with Python, SQL, and big data tools. This position offers a dynamic environment with opportunities to significantly impact data-driven innovations.

Formación

• 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.

Responsabilidades

• Identify critical data sources and define ML-relevant features.
• Build scalable data lakes/databases for cross-org data access.
• Develop and maintain reproducible ETL/ELT pipelines.

Conocimientos

Python

SQL

Data manipulation libraries

Big data tools

Cloud platforms

Statistics

ML workflows

Data governance

Educación

Master’s in Data Science or related field

Herramientas

Snowflake

Spark

Kubernetes

Docker

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