Lead Data Engineer [JRD-399]

Intellias; Almería; A distancia; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

A technology company is looking for a Lead Data Engineer for a remote position in Spain. You will lead a data engineering team, design data models, and implement ETL processes. The ideal candidate has over 5 years of experience in data engineering, with strong skills in Python and AWS. This role offers an opportunity to work on transformative data platforms that support AI and real-time decision-making.

Formación

• 5+ years of hands-on experience in data engineering with Python and SQL.
• 3+ years of experience with AWS (Glue, S3, Athena, Lambda, DataZone).
• Strong experience with Airflow and Spark.

Responsabilidades

• Lead a data engineering team.
• Collaborate with business stakeholders to analyze data requirements.
• Design and implement data models and database structures.

Conocimientos

Data engineering

Python

SQL

AWS

Airflow

Spark

CI/CD

NoSQL

Descripción del empleo

Lead Data Engineer

Location: Remote from Spain

Join a transformative data and AI platform initiative aimed at modernizing enterprise-scale capabilities and enabling real-time decision-making. This project delivers a comprehensive roadmap covering AI, MLOps, data governance, and platform scalability, supporting a shift towards data-first operations and intelligent automation.

Requirements:

1. 5+ years of hands-on experience in data engineering with Python and SQL.
2. 3+ years of experience with AWS (Glue, S3, Athena, Lambda, DataZone).
3. Strong experience with Airflow and Spark.
4. Drive the design and implementation of data warehouse and data lakes.
5. Proficient in code versioning (git) and building CI/CD for data projects.
6. Experience with requirement gathering and documentation.

Will be a plus:

• Experience with NoSQL.

Responsibilities:

1. Lead a data engineering team.
2. Collaborate with business stakeholders and technical teams to understand and analyze data requirements.
3. Lead the design and implementation of data models and database structures that meet business needs.
4. Profile, refactor, and tune performance in the database.
5. Design and implement complex ETL processes to extract, transform, and load data from various source systems into the data warehouse.
6. Ensure data integrity, consistency, and accuracy through robust data quality assurance measures.
7. Review and support team members, providing guidance and mentorship.
8. Supervise and contribute to the data-driven strategy for the project, aligning it with business objectives.