Software Engineer - Global Feature Store (Machine Learning Platform)

TN Spain; Barcelona; Presencial; EUR 40.000 - 80.000; Jornada completa

Descripción de la vacante

An innovative firm is seeking a talented Software Engineer to join their Global Feature Store team in Barcelona. This role involves designing and implementing robust solutions for a data-intensive service, contributing to product development, and ensuring system reliability. The ideal candidate will have a strong background in programming languages like Java, Kotlin, or Python, and a keen interest in data management and machine learning. Join a dynamic environment where your skills will directly impact high-traffic platforms and contribute to exciting projects across various markets. If you are passionate about technology and eager to make a difference, this opportunity is perfect for you.

Formación

• Degree in Computer Science or relevant experience required.
• Strong interest in data-intensive application development is essential.

Responsabilidades

• Design and implement scalable solutions for high-traffic platforms.
• Contribute to product development and lead impactful projects.

Conocimientos

Java

Kotlin

Python

Analytical Skills

Problem-Solving Skills

Communication Skills

Educación

Degree in Computer Science

Herramientas

Relational Databases

Machine Learning

Descripción del empleo

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Software Engineer - Global Feature Store (Machine Learning Platform), Barcelona

Client: Delivery Hero

Location: Barcelona, Spain

Job Category: Other

EU work permit required: Yes

Job Description:

We are looking for a highly skilled and passionate software engineer to join the Global Feature Store team at Glovo.

The Feature Store is a key component of Delivery Hero’s Machine Learning stack, allowing Data Scientists easy and consistent access to model features at training and serving time and reducing the duplication of feature engineering efforts across teams. Our Feature Store also powers backend engineering use cases which require low latency access to data in our Data Lake, vastly reducing development time of these projects and allowing feature discoverability and reusage across the organization.

Our team builds and operates the Global Feature Store not only in Glovo but also the rest of the brands in Delivery Hero, our parent company. Your solutions will be used across different use cases, ranging from logistics, fraud detection, ranking, etc. in all the markets Delivery Hero and Glovo operate in.

THE JOURNEY

1. Design and implement scalable, robust and innovative solutions for one of Delivery Hero’s busiest and most data-intensive services, where your expertise will shape the future of high-traffic platforms.
2. Actively contribute to our product development roadmap and lead high-impact projects.
3. Keep our tier-1 system up and running ensuring that our business runs smoothly.
4. Develop software using modern engineering approaches and agile principles.
5. Make our technology and our team scale as the business grows.
6. Own your deliverables from start to finish and deliver high-quality solutions.

Qualifications

1. A degree in Computer Science or relevant experience.
2. Experience diagnosing and resolving performance problems in complex software systems.
3. Strong interest and experience in data-intensive application development.
4. Familiarity with the Machine Learning lifecycle.
5. Strong Java/Kotlin/Python or other high-level language skills.
6. Extensive knowledge of object-oriented programming and software architecture.
7. Knowledge of relational databases, and other approaches to data management.
8. Knowledge of concurrency and Event-Driven Development.
9. Analytical and problem-solving skills.
10. Vivid interest in at least one area outside of coding (architecture, algorithms, optimization, automation, scalability, etc.).
11. You have strong written and verbal communication skills in English.

Nice to have:

1. Experience in fast-growing tech companies and scaleups.
2. Proficiency in software architectures and performance optimization techniques.
3. Past work experience in the field of data engineering, data science or streaming analytics.