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Staff Engineer | Tracking

OLX

Barcelona

Presencial

EUR 50.000 - 70.000

Jornada completa

Hace 30+ días

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Descripción de la vacante

An established industry player is seeking a Staff Engineer for their Data Engineering team in Barcelona. This role offers the chance to re-architect the Tracking framework, enhancing data accuracy across multiple platforms. With over 7 years of experience in backend technologies like Python, Kotlin, and Java, you'll collaborate with data engineers and product managers to design solutions that improve user behavior measurement. If you're passionate about building scalable systems and enjoy problem-solving in a collaborative environment, this position is perfect for you. Join a dynamic team and make a significant impact on data accuracy and user insights.

Formación

  • 7+ years of experience in software development with backend technologies.
  • Strong understanding of software design and architectural patterns.

Responsabilidades

  • Rethink and re-architect the Tracking framework to enhance accuracy.
  • Design an implementation framework to address tracking pain points.

Conocimientos

Backend Development
Python
Kotlin
Java
Go
RESTful APIs
Software Design
Problem-Solving
Analytical Skills

Educación

Bachelor's degree in Computer Science
Master's degree in Computer Science

Herramientas

GA4
AWS
CI/CD
Data Catalog

Descripción del empleo

Barcelona, Spain

OLX – Engineering / Full-time / On-site

A Staff Engineer position is available in the Data Engineering team, Data Platform. Reporting to the Head of Data Engineering, you will be able to rethink and re-architect the Tracking framework of OLX with the objective of increasing its accuracy. You will work alongside a team of data engineers, software engineers and a PM dedicated to Tracking.

What will you be doing

  1. Understand the general architecture of our web platforms for all countries / businesses (OLX, Real Estate, Motors) and identify the pain points where tracking may be different or difficult to transmit information between a certain codebase to another;
  2. Design an implementation framework that will match the technical reality of all CUs and propose solutions to all pain points identified that will positively impact our efficiency in measuring accurately our user behaviour. You’ll have the support of our chief data officer as well as engineering managers;
  3. Ideally, the framework should be designed to push metadata from the code to our Data Catalog solution (instead of doing manual work on event / properties creation);
  4. With the help of product analytics & data service teams, you’ll help in coordinating potential implementation changes required to make tracking accuracy better (change event types in the code, fix implementation mistakes, wrong properties values, transmission of information cross codebase);
  5. Additionally, you’ll have the opportunity to audit the implementation of GA4 and provide guidance on leveraging value to this tool.

Who are we looking for

  1. Bachelor's or Master's degree in Computer Science or a related field;
  2. 7+ years of professional experience in software development with expertise in backend technologies (Python, Kotlin / Java, Go);
  3. Experience with RESTful APIs and integrating them into applications;
  4. Strong understanding of software design, object orientation, architectural patterns, and delivery patterns;
  5. Familiarity with the mobile ecosystem, the full mobile development life-cycle, common libraries, and languages;
  6. Experience in testing automation (unit testing, end-to-end testing);
  7. Familiarity with CI / CD processes and cloud native solutions, AWS is a plus;
  8. Passion for architecting, building, and scaling distributed systems;
  9. Excellent problem-solving skills and the ability to work in a collaborative team environment;
  10. Belief in self-aligned teams and the 'you build it, you run it' philosophy;
  11. Experience with metadata management and product analytics tools;
  12. Strong analytical skills to identify and resolve tracking inconsistencies and enhance data accuracy.
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