Data Engineer

Antal International; Madrid; On-site; EUR 70,000 - 95,000; Full time

Job summary

Antal International is seeking a Senior Data Engineer to join a distributed team within a software company. The role focuses on simplifying data architecture, raising quality standards, and delivering data products ready for analytics, reporting, and AI.

You will work with SQL, Python, and modern tools (Databricks, Airflow, dbt, Snowflake) to design scalable data pipelines and models. A strong product mindset and collaboration with BI/product teams are essential.

Qualifications

• At least 4 years as a Data Engineer with SQL and Python.
• Hands-on with Databricks, Airflow, dbt and Snowflake.
• Strong analytical skills and product mindset.
• Knowledge of data modeling, version control, CI/CD, observability, and data quality.
• Experience applying generative AI or ML to accelerate engineering tasks is highly valued.

Responsibilities

• Orchestrate processes with Airflow, including monitoring, alerting, retries, and quality checks.
• Design and evolve analytical models with dbt, ensuring modularity, testing, documentation, and lineage.

Skills

SQL

Python

Data modeling

CI/CD

Observability

Data quality

Generative AI experience

Tools

Databricks

Airflow

dbt

Snowflake

Job description

We are looking for a Senior Data Engineer with at least 4 years of proven experience in data engineering to join a distributed team embedded within a software company, with the goal of simplifying the data architecture, raising quality standards, and accelerating the delivery of data products ready for analytics, reporting, and artificial intelligence.

Our client is a software company offering real engineering challenges at scale, operating within a cross-functional environment that spans Data Engineering, BI, and product teams.

Requirements

• Demonstrable experience of at least 4 years as a Data Engineer, with strong command of SQL and Python, and the ability to design transformations that are clear, efficient, and testable.
• Hands-on proficiency with the technology stack: Databricks, Airflow, dbt, and Snowflake.
• Strong analytical skills to tackle complex problems, propose alternatives, and communicate technical decisions clearly. Product mindset and a focus on continuous improvement.
• Knowledge of data modeling, version control, CI/CD, observability, and data quality.
• Highly valued: experience applying generative AI or machine learning to accelerate engineering tasks or enable new data products.

Responsibilities

• Orchestrate processes with Airflow, incorporating monitoring, alerting, retries, and quality checks.
• Design and evolve analytical models with dbt, applying best practices in modularity, testing, documentation, and lineage.
• Contribute to defining layered architectures and data contracts that facilitate consumption by BI, analytics, and AI.
• Optimize performance, cost, and reliability of pipelines, helping identify technical debt and opportunities for simplification.
• Work with business, BI, and platform stakeholders to translate real needs into sustainable data solutions.
• Explore and apply AI use cases that improve development, quality, or documentation.

What we offer

• Permanent contract.
• Career development and personalized training.
• Real challenges in architecture, quality, automation, and scalability.
• Cross-functional way of working alongside Data Engineering, BI/Reporting, and other product and technology teams.