Senior Data Engineer - Cloud Data Lake & Streaming

Parser; Madrid; Presencial; EUR 65.000 - 105.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Knowledge sharing culture

Descripción de la vacante

Parser is seeking a Senior Data Engineer to join a fast-growing team delivering data-driven decisions across the business. You will ingest, enrich, and transform billions of messages daily to enable analytics for internal functions and services.

You will work with a cloud-based data lake stack including Kafka, Spark, Scala, Airflow, Hive, Kinesis, EMR, and Docker, and you will help design scalable, highly available systems while collaborating with cross-functional teams.

Formación

• 6-7 years of experience with at least one modern programming language (Python or Scala).
• Experience delivering highly available and scalable solutions with large transaction volumes.
• Strong SQL proficiency and experience with relational and non-relational databases.
• Experience using cloud services (AWS preferred).
• Passion for learning, especially in data, architecture and patterns.
• Ability to work in a multidisciplinary agile team.

Responsabilidades

• Develop data capture, processing, storage, distribution, and visualization components.
• Apply AWS standard methodologies and products (compute, storage, databases).
• Write clean, maintainable, and well-tested code.
• Develop scalable distributed systems emphasizing availability, monitoring, and resiliency.
• Communicate and document solutions and design decisions.
• Propose new approaches and contribute to system architecture.
• Be part of an agile team that is continuously learning and improving.

Conocimientos

Python

Scala

SQL

AWS

Herramientas

Kafka

Spark

Airflow

Hive

Kinesis

EMR

Docker

Descripción del empleo

Parser is seeking a Senior Data Engineer to join a fast-growing team delivering data-driven decisions across the business. You will ingest, enrich, and transform billions of messages daily to enable analytics for internal functions and services.

You will work with a cloud-based data lake stack including Kafka, Spark, Scala, Airflow, Hive, Kinesis, EMR, and Docker, and you will help design scalable, highly available systems while collaborating with cross-functional teams.