Data Engineer

We are looking for a Data Engineer with at least 5 years of experience to design, build, and optimize scalable data platforms and pipelines.

The role combines hands-on data engineering with technical ownership, including real-time data processing, cloud data platforms, performance and cost optimization, and collaboration with Data Science and Machine Learning teams.

The position follows a hybrid working model in Valencia, Spain.

Responsibilities

• Design and implement scalable data architectures and data pipelines.
• Lead data platform development and technical initiatives.
• Build real-time streaming and data processing solutions.
• Optimize data pipelines for performance, scalability, and cost.
• Collaborate with Data Science and ML teams on data and machine learning pipelines.
• Promote data engineering best practices and mentor junior engineers.

Requirements

• 5+ years of experience in Data Engineering.
• Experience with Big Data technologies such as Spark, Kafka, and Hadoop.
• Experience with cloud data platforms such as Snowflake, Databricks, or BigQuery.
• Experience with orchestration tools such as Airflow, Prefect, or Dagster.
• Knowledge of stream processing technologies such as Kafka Streams or Flink.
• Experience with data lake architectures.
• Knowledge of DataOps, MLOps, and Infrastructure as Code.
• Strong understanding of data pipeline performance and cost optimization.
• Ability to design scalable solutions and influence technical architecture decisions.
• Availability to work in a hybrid model in Valencia, Spain.

Nice to have

• Knowledge of Data Mesh and Data Fabric concepts.
• Experience with enterprise data platform architecture.
• Knowledge of data governance and compliance.
• Experience evaluating data technologies and vendors.
• Exposure to enterprise data platform transformation initiatives.

We are looking for a Data Engineer with at least 5 years of experience to design, build, and optimize scalable data platforms and pipelines., * 5+ years of experience in Data Engineering.

• Experience with Big Data technologies such as Spark, Kafka, and Hadoop.
• Experience with cloud data platforms such as Snowflake, Databricks, or BigQuery.
• Experience with orchestration tools such as Airflow, Prefect, or Dagster.
• Knowledge of stream processing technologies such as Kafka Streams or Flink.
• Experience with data lake architectures.
• Knowledge of DataOps, MLOps, and Infrastructure as Code.
• Strong understanding of data pipeline performance and cost optimization.
• Ability to design scalable solutions and influence technical architecture decisions.
• Availability to work in a hybrid model in Valencia, Spain.

Nice to have

• Knowledge of Data Mesh and Data Fabric concepts.
• Experience with enterprise data platform architecture.
• Knowledge of data governance and compliance.
• Experience evaluating data technologies and vendors.
• Exposure to enterprise data platform transformation initiatives.