3 months ago
Málaga, SpainStaff+
Responsibilities
- Lead the technical design and implementation of large-scale data processing and streaming applications.
- Define architecture standards and best practices for distributed data platforms.
- Design, develop, and optimize batch and real-time data pipelines with Apache Spark and Kafka.
- Build and maintain scalable APIs following OpenAPI specifications.
- Analyze systems, identify performance bottlenecks, and implement optimization strategies.
- Collaborate with product owners, architects, data engineers, and business stakeholders on technical solutions.
- Mentor developers through code reviews, technical guidance, and knowledge sharing.
- Drive technical decisions, roadmap planning, engineering improvements, and platform reliability.
Requirements
- Strong enterprise Java development experience.
- Expertise in Apache Spark, including Spark SQL, Spark Structured Streaming, and distributed data processing.
- Hands-on experience with the Cloudera ecosystem and Apache Kafka, including Kafka Streams.
- Experience developing applications with Scala.
- Expertise designing and implementing RESTful APIs using OpenAPI specifications.
- Strong understanding of SQL databases and data modeling.
- Experience with cloud platforms, particularly AWS, and hands-on Databricks experience.
- Experience leading technical teams and complex software projects, making architectural decisions, and providing technical direction.
- Experience mentoring developers and promoting engineering best practices.
- Preferred: experience with cloud-native architectures, microservices, DevOps practices, data governance, monitoring, and observability frameworks.
Benefits
- Permanent, full-time contract with career development opportunities.
- International projects in a multicultural environment, including exposure to large-scale financial IT systems and cross-country operations.
- Training opportunities in finance, technology, and data management.
Tech Stack
Categories
Data Engineering
