Lead Data Engineer

Dimática; Málaga; A distancia; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

DIMÁTICA, a recognized Microsoft PARTNER, seeks a Lead Data Engineer for their remote team to spearhead the architecture of scalable data pipelines using GCP and Snowflake. You will lead key data integration and modeling initiatives while mentoring fellow engineers, ensuring the integrity and scalability of the data infrastructure. Ideal candidates are tech-savvy leaders with a passion for data-driven solutions.

Formación

• Experience with cloud technologies like GCP and Snowflake is essential.
• Proven record in leading data engineering initiatives and teams.
• Strong focus on quality, performance, and security in data architectures.

Responsabilidades

• Design, develop, and optimize data pipelines using dbt, Fivetran, and Airflow.
• Lead data integration, modeling, and governance initiatives.
• Document data architectures and processes for future scaling.

Conocimientos

Data Integration

Data Modeling

Data Governance

Cloud Infrastructure

Technical Leadership

Herramientas

dbt

Fivetran

Airflow

GCP

Snowflake

Descripción del empleo

At DIMÁTICA, a company recognized as a Microsoft PARTNER, we specialize in the design, development, and maintenance of software solutions across multiplatform environments.

We're looking for a Lead Data Engineer to join our remote team, leading the architecture and development of scalable data pipelines on GCP and Snowflake.

What You'll Do

• Design, develop, and optimize robust data pipelines using technologies such as dbt, Fivetran, and Airflow.
• Lead data integration, modeling, and governance initiatives in close collaboration with product, analytics, and data science teams.
• Act as a technical leader and mentor to other engineers, with a strong focus on quality, performance, and security.
• Ensure the reliability and scalability of our cloud-based data infrastructure.
• Document data architectures, flows, and processes to support maintenance and future scaling of the data ecosystem.