Hands-On Data Engineering Lead – Madrid (Remote)

MediaRadar, Inc.; Madrid; Hybrid; EUR 110,000 - 150,000; Full time

Job summary

MediaRadar, based in Madrid, is seeking a Data Engineering Manager to own the data delivery lifecycle. This is a hands-on leadership role where you’ll write code, design schemas, and mentor a growing team of data engineers.

You’ll help move the stack toward open-source tooling on AWS, architect scalable ETL/ELT pipelines, and ensure reliable data delivery while championing AI-assisted development practices.

Qualifications

• 6-8+ years in data engineering with hands-on coding.
• Strong SQL and RDBMS experience.
• Experience with dbt, ClickHouse and orchestration tools like Airflow/Dagster.
• Proficient in Python for building data pipelines.
• Experience with AI coding assistants and prompting techniques.
• Experience with AWS or major cloud platforms.
• Bachelor's or Master's in CS/Engineering.
• Professional fluency in English.

Responsibilities

• Lead and mentor Madrid data engineers while providing technical direction.
• Design and optimize large-scale ETL/ELT pipelines with hands-on coding.
• Develop proofs-of-concept for new tools like ClickHouse/dbt.
• Drive platform modernization toward an open-source AWS-based stack.
• Ensure data quality, testing, monitoring, and CI/CD practices.
• Collaborate with global teams across North America, India, and Europe.
• Advance AI-assisted development practices and standards.

Skills

SQL & relational databases

Python

Data pipelines

Git & code reviews

AI-assisted development

Cloud: AWS

Team leadership (hands-on)

Communication

Education

Bachelor's or Master's in Computer Science/Engineering

Tools

dbt

ClickHouse

Airflow

Dagster

Git

Terraform

Job description

MediaRadar, based in Madrid, is seeking a Data Engineering Manager to own the data delivery lifecycle. This is a hands-on leadership role where you’ll write code, design schemas, and mentor a growing team of data engineers.

You’ll help move the stack toward open-source tooling on AWS, architect scalable ETL/ELT pipelines, and ensure reliable data delivery while championing AI-assisted development practices.