We are looking for someone to join our Data department as a Data Engineer, helping us manage the integration and consolidation processes of our clients' data. In both on-premise and cloud environments, you will be responsible for designing the required information system architecture and managing and maintaining our clients' databases.

We’re looking for a proactive and analytical person who can adapt to a multidisciplinary team and is eager to help us tackle the many challenges our clients face.

What are we looking for?

Education:

• University degree in Computer Science, Software Engineering, or related fields with a technological specialization in data analysis and engineering.
• Plus: Master's or postgraduate degree in Big Data, Machine Learning, Cloud Computing, or Data Engineering.
  
  

Required Experience (demonstrable and advanced):

• Data Architecture & Systems: Extensive experience in designing, implementing, and optimizing complex, distributed information system architectures, including relational and NoSQL databases.
• Cloud Environments: Deep expertise in defining, implementing, managing, and maintaining enterprise-scale Cloud environments. Expert command of Azure and Google Cloud Platform (GCP), including PaaS/SaaS, serverless computing (Functions, Cloud Run, Azure Functions), containers (Docker, Kubernetes/AKS/GKE), and native cloud data services.
• Modern Data Warehouses: Advanced experience with cloud-native Data Warehouses like Snowflake, including dimensional data modeling, query optimization, and cost/performance management.
• Data Orchestration & Pipelines: Robust experience with data orchestration tools and building complex ETL/ELT pipelines using Pentaho, Apache Airflow, Data Factory, or similar, including CI/CD implementation for data pipelines.
• Advanced SQL: Demonstrable experience with advanced SQL, including complex analytical functions, query optimization, stored procedures, and efficient schema design.
• Software Development: Demonstrable experience with Javascript and Node.js, and Python for scripting, data automation, and ML model development.
  
  

Desired Experience:

• Customer Data Platforms (CDP): Experience in strategic definition, implementation, management, and maintenance of CDP solutions, preferably Segment, and their integration.
• Enterprise System Integration: Desirable experience with enterprise-level integration tools like Mulesoft or microservices architectures with REST/GraphQL APIs.
• Salesforce Ecosystem: Valuable experience working with Salesforce (Sales Cloud, Service Cloud, Marketing Cloud – SFMC), including data integration and automation.
  
  

Knowledge (Essential and Valuable):

• Deep knowledge and certifications in managing and optimizing cloud environments (Azure, GCP).
• Advanced knowledge and certifications in Snowflake (SnowPro Advanced/Architect is a plus).
• Proficiency in CDP tools (especially Segment).
• Knowledge of CRM / Marketing Automation tools (SFDC, SFMC, Adobe Campaign, Selligent Marketing Cloud).
• Advanced SQL knowledge (Analytical Functions, T-SQL, PL/SQL).
• Proficiency in programming languages like Javascript, Node.js, and Python.
• Strong understanding of Data Quality principles, Data Governance, and Normalization.
• Solid understanding of Machine Learning and AI algorithms for data enrichment and transformation.
• Experience with data streaming architectures (Kafka, Pub/Sub, Azure Event Hubs).
• Familiarity with MLOps and DataOps concepts.
  
  

Skills:

• Ability to analyze and solve complex problems.
• Project management and organizational skills for end-to-end data projects.
• Meticulous attention to detail and commitment to data quality.
• High capacity for discernment and prioritization in dynamic environments.
• Technical leadership and mentoring of junior profiles.
• Strategic thinking and innovation-oriented mindset.
• Excellent communication and presentation skills for clients and multidisciplinary teams.
  
  

Languages:

• Spanish (Native or Bilingual proficiency).
• English (High level C1/C2 - Essential for communication with international clients).
  
  

What would you do in this role? Here’s a list of responsibilities and tasks:

• Lead strategic requirements gathering, high-level design, and implementation of complex data solutions for client communication initiatives.
• Design and evolve scalable, efficient data architectures, selecting appropriate cloud-native technologies for each project.
• Design, develop, and optimize ETL/ELT data integration processes to ensure high-quality data ingestion, transformation, and availability.
• Implement end-to-end data solutions, ensuring validation, thorough documentation, and adherence to best practices in data engineering and security.
• Provide training and knowledge transfer to internal teams and clients.
• Maintain, evolve, and optimize existing data projects, ensuring monitoring, incident resolution, and continuous improvement.
• Manage and optimize client databases, ensuring performance, integrity, and security.
• Innovate with AI/ML: Implement data cleansing, normalization, consolidation, deduplication, and enrichment systems using ML/AI algorithms, including predictive scoring and customer clustering.
• Ensure Data Quality and Governance: Implement DQ mechanisms, guarantee data integrity, and ensure GDPR compliance across all processes.
• Strategically collaborate with clients: Participate in high-level meetings to assess current information system architectures, propose innovative improvements, and lead solution definitions for future challenges and new data platforms.
• Mentor and guide other data engineers, fostering best practices and professional development.
  
  

And since you'll give this and much more, we also want to give you much more:

• A dynamic and creative work environment.
• Important clients and international brands.
• Full-time position.
• Hybrid format.
• Christmas, Easter, July, and August: FULL REMOTE
• Flexible hours.
• Permanent contract with a six-month trial period.
• 22 working days of vacation per year + 12 extra days!
• Optional access to flexible compensation (health insurance, transportation, meals, and childcare).
• Ogilvy Wellness Program: Free psychological, legal, and financial support service. Discounts on physiotherapy and gyms.
• Ogilvy is recognized with the Family-Responsible Company (EFR) certification for its commitment to employee well-being and work-life balance.
  
  

If you’ve imagined yourself in this position, that’s a good sign. At Ogilvy, we want to work with the best talent—those who challenge us and make us better. People who are eager to experience an agency culture open to diversity as a principle and connectivity as a primary tool.

So, if you're nodding your head while reading this, send us your CV!

Wallapop is a Barcelona based scale-up driven by the purpose to empower people to embrace a more conscious and human way of consumption. We believe in a world where collaborative economy is mainstream. This is what drives us. 💫

Wallapop operates in Spain, Italy and Portugal, offering a catalogue of several hundreds of millions of products and services. Powered by technical innovation and continuous improvement, we bring together the scale & trust of classifieds with the marketplace’s convenience & reach. 🌱 Our mission is to enable a connected trade ecosystem, making 2nd-hand the norm through smart use of technology.

The Challenge 🧩 

Wallapop generates billions of data points daily. With a mature data infrastructure already in place, our Data Science and Machine Learning area is gaining significant momentum. As we scale, we face the exciting challenge of taking our ML Platform to the next level to support complex solutions in Personalization, Search, Trust & Safety, and Logistics. As a Senior ML Engineer, you will lead the evolution of our ML Platform and MLOps practice. You will partner with Data Scientists, Data Engineers, and DevOps to shape a vision that balances innovation with reliability, ensuring our models scale efficiently to serve millions of users.

What You Will Do 👇

• Iterate and maintain Wallapop’s ML Platform, identifying opportunities to improve speed, reliability, and maintainability. You will define the long-term vision and roadmap for MLOps.
• Work hand-in-hand with Data Scientists to support their efforts, ensuring they have the tooling to develop, deploy, and monitor scalable models efficiently.
• Define and promote engineering best practices (coding standards, testing, CI/CD) within the ML domain.
• Partner with Data Engineering and DevOps to align ML development with company-wide infrastructure and data governance standards.
• Investigate and integrate new frameworks and tools (e.g., for LLMs or real-time inference) to keep our stack modern and effective.

What We’re Looking For 🔎

• Proven experience building and owning production-ready ML platforms and pipelines. You understand the full lifecycle from experimentation to monitoring.
• Deep understanding of AWS components (SageMaker, Lambda, S3) and container orchestration with Kubernetes.
• Strong software engineering background with proficiency in Python, Git, and CI/CD workflows. You write robust, testable code.
• Experience with real-time ML architectures, leveraging tools like Kafka for low-latency ingestion and inference.
• Hands-on experience with vector databases or semantic search infrastructure (e.g., OpenSearch, Vertex AI), including indexing and retrieval tuning.
• Familiarity with the broader ML toolkit, such as orchestration/tracking tools (Flyte, MLFlow, Feast) and standard libraries (Pandas, Scikit-learn, TensorFlow/PyTorch).
• Professional proficiency in English, with the ability to explain complex technical concepts to diverse stakeholders.

What Would Be A Plus 🚀

• Hands-on experience working with LLMs, RAG architectures, and libraries like LangChain or LlamaIndex.
• Familiarity with Big Data technologies like Spark or Beam.
• Experience with Data Engineering tools such as Airflow, dbt, or Datahub.
• Experience with other cloud platforms like GCP or Azure in addition to AWS.

Do note that all our jobs are 📍 Barcelona based. We follow a hybrid model where flexibility rules. We commit to a minimum of 6 days per month in the office. Each team self-organizes to decide on cadence and in-person/remote rituals.

Wallapop is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees as we want Wallapop to be a place for everyone.

Additionally to the opportunity to contribute to an agile product set up and work together towards achieving our meaningful mission, we offer the following 🍭 Perks & Benefits:

• Generous individual learning budget of 2k per year
• Free office meals, lunch selection from different providers
• Group and individual English, Catalan & Spanish lessons as part of our working day
• Private Health Insurance with Alan
• Flexible working hours + intensive Fridays
• Flexible remuneration to deduct from gross salary (kindergarten/food/transport check)
• Gym & Wellness plan, including physiotherapist in the office
• Generous referral Program & Charity Donation
• Bonus for weddings & newborns
• Wallapop Renta (Tax income support)
• Monthly plan for free shipping, bumps & home-pick-up on our services
• Work anniversary Gifts and Birthday Surprises
• Contribution towards your WIFI in your monthly payroll
• One-off payment based on compensation package to go towards setting up your home office
• Relocation package (monetary support and legal advice) and visa sponsorship, if applicable
• 26 holidays per year
• TOP hardware of your choice (latest Apple or Windows)

What does the hiring process for this position look like? 👀 **Please, note that all interviews take place remotely over hangouts.**

• Intro Call - run by Talent Acquisition, focus on providing more information about the role and the company as well as going over your experience, motivation, and expectations. This usually takes 45-60 minutes.
• Technical Task - you will be assigned a challenge to assess the technical skills required for the role.
• Expertise Interview - run by the core team, focusing on the hard skills and the ability to deliver in a given context. This usually takes 60-90 minutes.
• Stakeholder Interview - run by the hiring team and relevant stakeholders, focus on the ability to collaborate & deliver in a cross-functional set-up. This usually takes 60 minutes.
• Culture-Add Interview - run by culture interviewers, focus on adherence to Wallapop's purpose and business proposition. This usually takes 60 minutes.
• Offer - should you be the right candidate, your offer will be discussed over a call with talent acquisition and will then be confirmed in writing.

Wallapop is a Barcelona based scale-up driven by the purpose to empower people to embrace a more conscious and human way of consumption. We believe in a world where collaborative economy is mainstream. This is what drives us💫.

Wallapop operates in Spain, Italy and Portugal, offering a catalogue of several hundreds of millions of products and services. Powered by technical innovation and continuous improvement, we bring together the scale & trust of classifieds with the marketplace’s convenience & reach. Our mission is to enable a connected trade ecosystem, making 2nd-hand the norm through smart use of technology.

The Challenge 🧩

Our platform generates vast amounts of data. With a mature infrastructure already in place and a growing team, the opportunities to make a tangible impact are endless. As a Data Scientist, you will improve marketplace dynamics by working on end-to-end ML solutions—from data gathering and prototyping to deployment and iteration.

As a Data Scientist in the Wallapop you will be working on the Data Science and Machine Learning initiatives aimed at improving the whole marketplace dynamics. This will include topics such as improving models that power users' main interaction point:  Search.  You will also look into various models that will help users discover new items through ranked Recommendations, Similar Items, and more.

You will work closely with other Data Scientists, Product Managers, Engineers, UX Researchers, and Analysts to understand the product requirements and explore possible data and ML solutions. You will own the whole product lifecycle, from gathering the data needed to prototyping, building, evaluating, and iterating end-to-end solutions, all within Wallapop’s Data and ML Platforms.

Additionally, you will have the opportunity to work on internal research projects, exploring new technologies and building PoCs that could ultimately become data products or insights, and be valuable for Wallapop.

What You Will Do👇

• Collect, clean, and analyze large datasets from diverse sources, including user behavior, transactions, and market trends.
• Develop and implement machine learning models to solve business problems, such as personalized recommendations and search.
• Work with multidisciplinary Product teams to identify opportunities and gather requirements (both in terms of product and tech).
• Own initiatives from start to deployment:  ideation, data processing (ETL), modeling, testing, deployment, monitoring and iteration (w/ help from Engineering partners)
• Proactively suggest, research and prototype new ideas for data and ML solutions.
• Communicate complex data insights to both technical and non-technical audiences, including stakeholders involved in marketplace operations.

What We’re Looking For 🔍

• Experience working with Search, recommendations & Ranking models in production environments

• Problem-Solving Core: A degree in a quantitative field (Engineering, Math, Stats, Physics) or equivalent practical experience in data science.

• Software Mindset: Proficiency in Python and the ability to write clean, maintainable code for ML applications.

• Production Experience: A proven track record of building and deploying data products that solve business challenges in a production environment.

• Data Fluency: Advanced SQL skills and experience handling large datasets (knowledge of libraries like Pandas or Scikit-learn is highly valued).

• Growth Orientation: A desire to learn new technologies and an ability to adapt your technical approach to the problem at hand.

• Algorithmic Foundation: Solid understanding of Machine Learning fundamentals, specifically as they apply to personalization or recommender systems (e.g., collaborative filtering, content-based filtering, or deep learning for embeddings).

What Would Be A Plus 🚀 

• Experience working within an eCommerce or Marketplace platform, or in a product-tech company.
• Experience working within the Logistics, Trust & Safety or Customer Service domains.
• Experience working within the AWS cloud (Redshift, S3, Lambda), and with cloud MLaaS solutions such as Amazon SageMaker (preferably), but also Google Vertex AI, Microsoft Azure ML, and other MLOps tools (MLFlow, Flyte, Feast, Kubeflow, etc).

Do note that all our jobs are 📍 Barcelona based. We follow a hybrid model where flexibility rules. We commit to a minimum of 6 days per month in the office. Each team self-organizes to decide on cadence and in-person/remote rituals.

Wallapop is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees as we want Wallapop to be a place for everyone.

We sponsor visa processes for international candidates when applicable and provide legal & admin support along the process combined with a competitive relocation package.

Additionally to the opportunity to contribute to an agile product set up and work together towards achieving our meaningful mission, we offer the following 🍭 Perks & Benefits:

• Generous individual learning budget of 2k per year
• Free office meals, lunch selection from different providers
• Group and individual English, Catalan & Spanish lessons as part of our working day
• Private Health Insurance with Alan
• Flexible working hours + intensive Fridays
• Flexible remuneration to deduct from gross salary (kindergarten/food/transport check)
• Gym & Wellness plan, including physiotherapist in the office
• Generous referral Program & Charity Donation
• Bonus for weddings & newborns
• Wallapop Renta (Tax income support)
• Monthly product advantages (Wallapop Club)
• Work anniversary Gifts and Birthday Surprises
• Contribution towards your WIFI in your monthly payroll
• One-off payment based on compensation package to go towards setting up your home office
• Relocation package (monetary support and legal advice) and visa sponsorship, if applicable
• 26 holidays per year
• TOP hardware of your choice (latest Apple or Windows)

What does the hiring process for this position look like? 👀 **Please, note that all interviews take place remotely over hangouts.**

Intro Call - run by talent acquisition, focus on providing more information about the role and the company as well as going over your experience, motivation, and expectations. This usually takes 45-60 minutes.

Task - you will be assigned a task to submit within 5 up to 7 days where you will be able to showcase your expertise and technical skills required for the role.

Expertise Interview - run by the hiring team, focus on the required core skills and the ability to deliver in a given context. This usually takes 60-90 minutes.

Stakeholder Interview - run by relevant stakeholders reflecting the reality of the context of the role, focus on the ability to collaborate & deliver in a cross-functional set-up. This usually takes 60 minutes.

Culture Interview - run by culture interviewers, focus on adherence to Wallapop's purpose and business proposition. This usually takes 60 minutes. 

Offer - should you be the right candidate, your offer will be discussed over a call with talent acquisition and will then be confirmed in writing.

Scopely is looking for a Senior Data Scientist to join our Monopoly GO! game team in our Barcelona hub on a hybrid basis, or remotely in Spain or Portugal.

At Scopely, we care deeply about what we do and want to inspire play, every day. We are a global team of game lovers who are developing, publishing, and innovating the mobile games industry, connecting millions of people around the world daily.

What You Will Do 

As a Senior Data Scientist, you will play a key role in supporting game growth by leveraging data to build innovative, player-centric solutions. You won't just analyze data; you will own the lifecycle of data products — from identifying a player pain point to deploying a production-level solution.

• Product Vision & Strategy: Partner with Product Managers and Stakeholders to identify high-value opportunities, helping to define the data science roadmap for the one of the world’s biggest mobile games.
• End-to-End Ownership: Own the process of creating new data products, from initial inception and requirement gathering to technical design, productionalization, and monitoring.
• Player Insights: Analyze player behavior to understand how features impact the game economy, progression, social dynamics, and sentiment.
• Advanced Modeling: Design and implement A/B tests, forecasting, clustering, and ML models that don't just "predict," but provide actionable "decision intelligence."
• Technical Excellence: Provide technical expertise throughout the product life cycle, ensuring high quality, scalability, and efficiency in our Data & Insights team.
• Collaborative Delivery: Work across departments (Product Analytics, Engineering, LiveOps, Marketing) to ensure data solutions are integrated and driving real-world impact for our players.

What We’re Looking For

We want a creative, highly motivated individual who enjoys tackling ambiguous problems and "figuring it out" with practical, scalable solutions.

• Product Mindset: Outstanding problem-solving skills with a "user-first" mentality. You can conceptualize player behavior and determine the best metrics to measure success, even when data is messy or non-existent.
• Technical Stack: Advanced proficiency in Python and SQL. Experience with BI tools (Looker) and visualization libraries (Plotly, etc.).
• Data Engineering Savvy: Experience with data transformation at scale using dbt and Airflow.
• Production Experience: Proven track record of deploying data products to production (on GCS, AWS, or Azure) and implementing monitoring/alerting to ensure service quality.
• Scientific Rigor: Strong background in statistics, A/B testing methodology, and applying ML/AI to improve business understanding.
• Communication: Ability to translate complex methodologies into clear "so-whats" for non-technical stakeholders and business users.

Bonus Points

• Gaming Passion: A deep love for F2P mobile games and an understanding of game loops/economies.
• Specialized Knowledge: Familiarity with causal inference, Bayesian statistics, or MLOps platforms.
• Deep Learning & GenAI: Hands-on experience with LLMs, predictions using Transformers, or other Deep Learning architectures applied to behavioral data or content generation.

We are looking for a Senior MLOps Engineer to add to our Data team in Barcelona.

Join the User Acquisition MLOps team that builds the core ML backbone of Appodeal. We design and run the systems that power real-time predictions at massive scale, where every millisecond matters. Our work directly drives thousands of bidding operations each second, supporting a high‑throughput, low‑latency inference platform used across the company.

You will help shape and evolve a modern ML platform built around Databricks, MLflow, Unity Catalog, GitHub Actions, and deep integrations with our Predictor service. This means solving real engineering challenges: scaling training pipelines, optimizing GPU workloads, ensuring safe and automated model promotions, and keeping online inference reliable under extreme load.

You will collaborate daily with Data Science, Data Engineering, Runtime, DevOps, and Product, and you will fully own the systems and projects you touch. This is a role for engineers who like autonomy, impact, and building things that matter.

Responsibilities:

• Design, operate, and improve the ML platform, including Databricks workflows for training, MLflow and Unity Catalog for model management, CI/CD pipelines using GitHub Actions and Databricks Asset Bundles, and integration with the runtime inference layer.
• Support data scientists in developing and maintaining end-to-end training pipelines, covering data processing, feature transformations, ML model training on GPUs, and distributed training setups to ensure efficient and scalable workflows.
• Ensure reliable and safe model inference by validating models before promotion, checking metadata compatibility, monitoring latency, and supporting model evaluation flows.
• Maintain strong ML observability, including online and offline monitoring, data and feature parity checks, and automated validation of model performance in production.
• Develop internal tools and APIs that enable DS teams and account managers to experiment, validate, and promote models efficiently while reducing operational friction.

Requirements:

• 3+ years of experience in MLOps, ML Platform Engineering, or Backend roles supporting production ML systems.
• Strong Python and software engineering skills, with experience building and maintaining APIs (FastAPI, Flask, or similar).
• Hands-on experience with DNNs using PyTorch or other modern deep learning frameworks, including GPU training and optimizing hardware utilization.
• Solid understanding of distributed computing and data processing using Apache Spark or similar frameworks.
• Experience with Databricks (Jobs, MLflow, Delta, UC) or an equivalent cloud-based ML platform.
• Strong understanding of the ML lifecycle: data ingestion, experimentation, model packaging, deployment, and monitoring.
• Familiarity with real-time model inference systems and ensuring compatibility with downstream services.
• Experience with data validation libraries (Pydantic or similar) used within ML and API workflows.
• Good understanding of Docker containers, Kubernetes, and basic networking concepts.
• Experience creating and maintaining CI/CD pipelines (GitHub Actions or similar).
• Experience with orchestration tools (Databricks Jobs, Dagster, Airflow or similar).
• Demonstrated ability to use modern AI tools (Claude, ChatGPT, Gemini) to improve development speed and quality.
• Proactive mindset with a strong sense of ownership, consistently pushing work forward and anticipating next steps without needing close direction.
• Strong English communication skills.

Nice to have:

• Exposure to very high-load, low-latency ML inference environments.
• Knowledge of distributed or large-scale ML training frameworks and multi-GPU setups.
• Familiarity with Databricks Asset Bundles.
• Understanding of ONNX or other portable model serialization formats.
• Ability to work with Rust programming language.
• Familiarity with transformer architectures, encoder-decoder models, or sequence modeling approaches.
• Exposure to data engineering concepts, such as building scalable data pipelines, understanding CDC patterns, or working with structured and unstructured datasets.
• Experience with MinIO or other S3-compatible storage systems.
• Understanding of networking protocols such as TCP, HTTP, and gRPC, including their limitations in low-latency scenarios.
• Confidence navigating the Atlassian ecosystem (Jira, Confluence, Compass).

This position supposes relocation to Barcelona and work from our office in the city center.

Why Join Us:

• Opportunity to work on cutting-edge projects with a global impact in the mobile app industry.
• A collaborative and inclusive work culture that values innovation and continuous learning.
• Competitive salary, flexible work arrangements, and a comprehensive benefits package.
• Professional development opportunities and career growth prospects within a fast-growing company.

About Appodeal

Appodeal is a dynamic US-based product company with a truly global presence.

We have offices in Warsaw, Barcelona, and Parkland (FL), along with remote team members located around the world.

Our company thrives on diversity, collaboration, and innovation, making us a leader in the mobile app monetization space.

Why Appodeal?

At Appodeal, we’re more than just a company—we’re a team united by a common mission:
Help people discover and grow their talents through products that enable successful mobile app businesses.

We take pride in our cutting-edge product and our internationally distributed team of talented professionals.

Here’s what we value:

• Continuous Learning and Growth – We invest in development and long-term careers
• Making an Impact – We are building a history-defining company in the mobile industry
• Solving Exciting Challenges – Complex, large-scale problems are part of our daily work
• Enjoying the Journey – We believe great results come with a positive environment

About the Role

We are looking for a Senior Rust Engineer to join our Barcelona team and contribute to building high-performance, real-time systems powering our ML-driven AdTech platform (Mobile Growth Platform).

In this role, you will work on core backend infrastructure and ML platform components, focusing on low-latency, high-load services that process large-scale traffic in real time.

You will play a key role in developing and optimizing systems such as real-time applications, feature stores, user identity services, and custom inference layers, ensuring scalability, reliability, and performance.

Responsibilities

• Contribute to the development of real-time applications and ML platform components
• Build and maintain high-load, low-latency backend services
• Work on in-house solutions including:
  • Feature stores
  • User identity services
  • Custom inference layer
  • ML platform infrastructure
• Optimize system performance across on-premise Docker & Kubernetes environments
• Design and implement solutions for traffic scaling and system reliability
• Collaborate with ML, data, and engineering teams to support production ML systems
• Continuously improve system architecture, observability, and efficiency

Tech Stack

• Languages: Rust, Python
• Data & Streaming: Kafka, SQL, Redis, ScyllaDB, Delta Lake, Databricks
• Infrastructure: Docker, Kubernetes (on-premise)
• Tools: GitHub

Requirements

• 5+ years of experience in software engineering
• Strong proficiency in Rust
  or
  proficiency in C/C++/Zig with willingness to transition to Rust
• Experience designing and building high-load, performance-critical systems
• Solid understanding of system design, concurrency, and performance optimization
• Basic knowledge of machine learning workflows and tools

Nice to Have

• System programming experience (C, C++, Zig)
• Experience in ML engineering / MLOps
• Strong Python skills
• Familiarity with AdTech standards (OpenRTB, MRAID, VAST)
• Experience with WASM / WASI
• Background in distributed systems and real-time processing
• Location: Barcelona, Spain (office attendance 4 days per week)

What We’re Looking For

• Autonomous and self-driven engineer with strong ownership mindset
• Passion for engineering excellence, performance, and scalability
• Interest in ML/AI systems and infrastructure
• Ability to work independently and make informed decisions
• Strong collaboration and communication skills

Why Join Us:

• Opportunity to work on cutting-edge projects with a global impact in the mobile app industry.
• A collaborative and inclusive work culture that values innovation and continuous learning.
• Competitive salary, flexible work arrangements, and a comprehensive benefits package.
• Professional development opportunities and career growth prospects within a fast-growing company.

We appreciate teamwork, critical thinking, independent decision-making, and standing up for oneʼs viewpoint.
We are looking for talented engineers who are willing to grow, improve and share our values!

We are now expanding our data capabilities and seeking an experienced Head / Director of Data Science to lead and scale our Data Science UA team function in Barcelona.

This role is ideal for a leader with a strong technical background, excellent people-management skills, and the ability to turn data into actionable, high-impact product and business outcomes.

Role Overview:

The Head / Director of Data Science will be responsible for building and growing our Data Science organization, driving advanced analytics and ML initiatives, and ensuring our products and business units are empowered by high-quality insights and predictive capabilities.

You will work closely with Product, Engineering, Revenue, and Leadership teams to translate business needs into DS/ML solutions, strengthen our data infrastructure, and support decision-making across the ecosystem.

This is a strategic and hands-on leadership role with significant influence on product evolution, optimization algorithms, and operational excellence.

Key Responsibilities:

Leadership & Strategy

• Lead and scale the Data Science function across the organization.
• Translate business and product goals into clear DS/ML initiatives and execution plans.
• Build and promote a strong data-driven culture across all teams.
• Applied Data Science & ML.
• Oversee development, deployment, and monitoring of ML models across Appodeal’s product and monetization ecosystem.
• Guide experimentation, modeling, uplift measurement, and algorithmic optimization.
• Ensure model quality, reliability, fairness, and performance at scale.
• Collaboration & Stakeholder Management.
• Partner with Product and Engineering teams to integrate Data Science into product roadmaps.
• Work with business units to identify opportunities, define DS/ML requirements, and deliver impactful insights.
• Communicate DS outcomes, metrics, and recommendations to leadership.

Team Leadership

• Lead, mentor, and develop a multidisciplinary team of Data Scientists, Analysts, and ML/AI specialists.
• Foster knowledge sharing, best practices, experimentation, and continuous improvement.
• Drive hiring, talent development, and team structure optimization.

Data Infrastructure & Governance

• Collaborate with Data Engineering and MLOps teams to ensure robust pipelines, feature stores, and model deployment workflows.
• Improve data quality, observability, and governance standards.

Qualifications:

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Math, or a related field (PhD is a plus).

Experience

• 5+ years of experience in Data Science, Machine Learning, or Applied Analytics.
• 3+ years in a DS leadership role (Lead DS, Head of DS, Director of DS, or similar).
• Demonstrated experience building and leading Data Science teams.
• Proven track record of delivering DS/ML solutions with real business impact.

Technical Skills

• Strong understanding of ML algorithms, experimentation, predictive modeling, and statistical analysis.
• Hands-on experience with Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and analytics tooling.
• Solid understanding of data pipelines, big data technologies, and collaboration with Data Engineering teams.
• Experience with AdTech, attribution, auction mechanics, or optimization algorithms is a strong plus.

Leadership & Soft Skills

• Excellent stakeholder management and communication skills.
• Ability to translate technical concepts into business language.
• Strong decision-making and prioritization abilities.
• Passion for mentoring, coaching, and building high-performing teams.

What We Offer:

• Opportunity to build and lead the Data Science function of a global product company.
• Direct influence on product roadmap and business outcomes.
• Collaborative and international team environment.
• Competitive compensation package and growth opportunities.
• A chance to shape the future of mobile app monetization.

Location: We are flexible! Come and join us either in Hamburg, Berlin or Barcelona. 

Freenow by Lyft empowers smarter mobility decisions helping people to move freely and cities to thrive.

The Freenow marketplace is a real-time, two-sided platform connecting millions of riders and drivers. Its efficiency and scalability are powered by a sophisticated ecosystem of Machine Learning systems spanning key domains such as Pricing, Allocation, and Marketplace Payment&Risk.

In this role, you’ll help advance our MLOps practices, build the services and the infrastructure that scales ML models from research to real-time production and observe how they impact the daily lives of our users and our business.

Be ready to work in a multinational, diverse, highly motivated and collaborative team of passionate developers who strive for excellence and like to have fun doing it.  Are you ready for your next ride?

YOUR DAILY ADVENTURES WILL INCLUDE:

• Developing and maintaining high-performance, distributed systems that serve ML models at scale with low latency
• Collaborating with Data scientists and Software Engineers to solve business-critical problems in real-time.
• Streamlining online serving for classical and deep learning models to accelerate A/B testing cycles and reduce time-to-market
• Enhancing our MLOps platform capabilities to support AI state of the art
• Implementing ML Monitoring and Observability best practices, including automated data drift detection and self-healing system triggers
• Contributing to the evolution of our MLOps stack and practices.

Our Techstack: Python | Airflow | Java | Kubernetes | Kafka | Databricks |AWS & more

TO BE SUCCESSFUL IN THIS ROLE:

• M.S or B.S in Computer Science, Machine Learning, Mathematics or equivalent technical background with related field
• 3+ years of professional experience deploying, scaling and monitoring ML models in production environment 
• Proficiency in Python. Experience in JVM based programming language (Java, Scala, Kotlin) or GO is highly desirable
• Proven experience with large-scale data processing systems and modern data warehousing 
• Strong grasp of classical ML and Fundamental understanding of modern ML algorithms (e.g. DNN, RL, transformers ) and mathematical optimizations e.g LP, Convex Optimization
• Team player, and an avid learner, with a proven capacity to collaborate seamlessly with diverse teams, including those in data, tech, and product, as well as other stakeholders.
• Clear Communication in English. We are a very diverse team with people from all over the world and English is our language of communication, besides Python.
• Passionate about harnessing Artificial Intelligence and have the will to play an essential role in the future of urban transportation.
• Experience with streaming technologies and real-time data processing (e.g., Apache Kafka, Apache Flink, Feature Stores) is a plus.

BENEFITS & PERKS IN A NUTSHELL:

DIVERSITY, EQUITY & INCLUSION:

Freenow is an equal opportunity employer and we consider qualified applicants regardless of race, religion, national origin, gender, gender identity, sexual orientation, disability or age.
We want you to grow and evolve, bring your true self to work. 

ABOUT US:

Freenow by Lyft empowers smarter mobility decisions, helping people to move freely and cities to thrive. Through our multi-mobility app, we feature broad options for everyone across 9 European markets and over 180 cities. Millions of passengers can access services including taxis, private hire vehicles, carsharing, car rental, e-scooters, e-bikes, e-mopeds, and public transport within a single app. 

In July 2025 Freenow was acquired by Lyft, a global mobility platform, which connects riders and drivers for billions of rides across North America and Europe. Together, Freenow and Lyft are creating a more caring and connected world, with transportation for everyone. We are a global, diverse, highly motivated, and collaborative team that strives for excellence and likes to have fun. Ready for your next ride?

Location: We are flexible! Come and join us either in Hamburg, Berlin or Barcelona. 

Freenow by Lyft empowers smarter mobility decisions helping people to move freely and cities to thrive.

The Freenow marketplace is a real-time, two-sided platform connecting millions of riders and drivers. Its efficiency and scalability are powered by a sophisticated ecosystem of Machine Learning systems spanning key domains such as Pricing, Allocation, and Marketplace Payment&Risk.

In this role, you’ll help advance our MLOps practices, build the services and the infrastructure that scales ML models from research to real-time production and observe how they impact the daily lives of our users and our business.

Be ready to work in a multinational, diverse, highly motivated and collaborative team of passionate developers who strive for excellence and like to have fun doing it.  Are you ready for your next ride?

YOUR DAILY ADVENTURES WILL INCLUDE:

• Developing and maintaining high-performance, distributed systems that serve ML models at scale with low latency
• Collaborating with Data scientists and Software Engineers to solve business-critical problems in real-time.
• Streamlining online serving for classical and deep learning models to accelerate A/B testing cycles and reduce time-to-market
• Enhancing our MLOps platform capabilities to support AI state of the art
• Implementing ML Monitoring and Observability best practices, including automated data drift detection and self-healing system triggers
• Contributing to the evolution of our MLOps stack and practices.

Our Techstack: Python | Airflow | Java | Kubernetes | Kafka | Databricks |AWS & more

TO BE SUCCESSFUL IN THIS ROLE:

• M.S or B.S in Computer Science, Machine Learning, Mathematics or equivalent technical background with related field
• 3+ years of professional experience deploying, scaling and monitoring ML models in production environment 
• Proficiency in Python. Experience in JVM based programming language (Java, Scala, Kotlin) or GO is highly desirable
• Proven experience with large-scale data processing systems and modern data warehousing 
• Strong grasp of classical ML and Fundamental understanding of modern ML algorithms (e.g. DNN, RL, transformers ) and mathematical optimizations e.g LP, Convex Optimization
• Team player, and an avid learner, with a proven capacity to collaborate seamlessly with diverse teams, including those in data, tech, and product, as well as other stakeholders.
• Clear Communication in English. We are a very diverse team with people from all over the world and English is our language of communication, besides Python.
• Passionate about harnessing Artificial Intelligence and have the will to play an essential role in the future of urban transportation.
• Experience with streaming technologies and real-time data processing (e.g., Apache Kafka, Apache Flink, Feature Stores) is a plus.

BENEFITS & PERKS IN A NUTSHELL:

DIVERSITY, EQUITY & INCLUSION:

Freenow is an equal opportunity employer and we consider qualified applicants regardless of race, religion, national origin, gender, gender identity, sexual orientation, disability or age.
We want you to grow and evolve, bring your true self to work. 

ABOUT US:

Freenow by Lyft empowers smarter mobility decisions, helping people to move freely and cities to thrive. Through our multi-mobility app, we feature broad options for everyone across 9 European markets and over 180 cities. Millions of passengers can access services including taxis, private hire vehicles, carsharing, car rental, e-scooters, e-bikes, e-mopeds, and public transport within a single app. 

In July 2025 Freenow was acquired by Lyft, a global mobility platform, which connects riders and drivers for billions of rides across North America and Europe. Together, Freenow and Lyft are creating a more caring and connected world, with transportation for everyone. We are a global, diverse, highly motivated, and collaborative team that strives for excellence and likes to have fun. Ready for your next ride?

We are currently looking for a Senior Data Engineer to join us remotely in Spain. You will work with our EMEA and US customers to help them solve their data engineering, ML, ML Ops, and cloud migration puzzles.

"As a Data Engineer at DATAPAO, you will have the unique opportunity to push the boundaries of technology and lead the way in how data transforms the world. We work with customers who want to innovate and change their industries. So it never gets boring! Sorting out a complex technical puzzle, setting up a new data architecture from scratch, or guiding our customers through adopting the latest technologies is our routine here. Hence, we'd expect you to be more than just a (data) engineer. We'd expect you to breathe and live data, to thrive for knowledge and excellence, and to be keen to build something enduring and impactful for our customers. We'd expect you to be a (data) Paoneer!"  (Máté Gulyás, CEO)

What will you do?

As a Senior Data Engineer, you are expected to deliver (across industries) on some of our most complex projects - individually or by leading small delivery teams. Although we work for the biggest multinational companies where years-long behemoth projects are the norm, our projects are fast-paced, typically 2 to 4 months long. Most are delivered using Apache Spark/Databricks on AWS/Azure and require you to directly manage the customer relationship alone or in collaboration with a Project Manager. Additionally, at this seniority level, we expect you to compound your impact across the team and the organization - by supporting our pre-sales process, mentoring more junior engineers, and contributing to hiring best-in-class data talent.

What does it take to fit the bill?

Technical Expertise

 Consulting & Client-Facing Skills

Operational Readiness & Soft Skills

• In a fast-paced consulting environment, where no two days are the same, flexibility and problem-solving comes naturally to you. Furthermore, resilience and thriving on challenges are essential traits in our industry;

What do we offer?

You'll have the rare opportunity to join DATAPAO at a time when you can still meaningfully impact our growth trajectory and organizational success. Furthermore, as our first-ever Spain hire, you could meaningfully contribute to expanding our local presence and, eventually, establishing a physical hub in this geography.

Surely, we know everyone needs a little something to do their best work. Here is a list of some other extras we offer:  

• The chance to work remotely - as we don't have a physical office in Spain yet, we offer a fully remote setup for the time being. However, given our strong community emphasis, we'd expect you to spend one month in our Budapest hub during onboarding and visit the office for one week every quarter;

• World-class educational benefits - there’s no shortage of learning opportunities at DATAPAO, meaning that you'll get access to Databricks' public and internal courses to learn all the tricks of Distributed Data Processing, MLOps, Apache Spark, Databricks, and Cloud Migration from the best. Additionally, we'll pay for various data & cloud certifications, you'll get dedicated time for learning during work hours, and access to our internal library; 

• Flexible PTO days - we’re flexible with how many days you take off if that does not conflict with customer success and the work getting done;

• Fully paid Medical Leave for up to 15 days per year - because when you’re unwell, we want you to focus on recovery and not worry about your paycheck;

• Comprehensive private health insurance plan via Allianz - offered via our EOR (Employer of Record) provider, Remote.com. Remote will be your official employer in Spain for the foreseeable future until we establish our own legal entity in Spain;

• Employee Assistance Program (EAP) via Allianz & Remote - life always happens! And we'd like to be there for you when it counts the most. Through EAP, we offer our employees access to psychology, financial, and legal consulting services via phone or in person;

• Top-notch working equipment - working comfortably means working well. You will get a MacBook Pro and a sign-up bonus of 500 EUR gross (to be paid with your first payroll) to set up your home office or whatever else is needed to give your best;

• The chance to make an impact in a high-transparency culture - open feedback and no politics are things we value a lot at DATAPAO. Additionally, you'll get the chance to work in the field of data & AI and shape the future of a rapidly growing tech company.

IMPORTANT NOTE: Given that we are still sorting our way in Spain, this list will likely get an update in the following months, and we're also committed to growing it with us over time.

The gross salary for this position ranges from 70.000 to 80.000 EUR/year, depending on your assessed seniority level during the selection process.

Please note that currently we are unable to support transfer or offer full sponsorship for Skilled Worker visas as we’re just setting foot into Spain.

We are seeking a skilled Data Engineer to join our Mobile Growth Platform UA team in Barcelona. The ideal candidate will be responsible for building, maintaining, and optimizing our data infrastructure, ensuring seamless data flow and accessibility for ML and DA, analytical and business needs.

Key Responsibilities:

• Design and build scalable data pipelines: Architect, construct, and maintain robust ETL/ELT pipelines using the Databricks platform (Apache Spark, Delta Lake, Delta Live Tables) for batch and streaming data ingestion from various sources.
• Manage data architecture: Define and maintain a scalable and secure data platform architecture that integrates Databricks (for data lakehouse management and complex transformations) with specialized OLAP engines (ClickHouse/Druid for fast querying).
• Design, develop, test, and orchestrate data workflows to streamline pipelines.
• Optimize performance and reliability: Monitor, troubleshoot, and fine-tune data workflows and database performance (e.g., Spark job optimization, ClickHouse schema tuning, Druid data partitioning) to ensure maximum efficiency and reliability.
• Contribute to the development of internal tools for automating data processes and business workflows, enhancing efficiency and scalability.
• Collaborate closely with product, MLOps and data science teams to ensure an optimal data experience for all ML practitioners and data consumers.

Requirements:

• 3-5+ years of professional work experience in data engineering.
• Strong expertise in Python and common data frameworks (Pandas, PySpark).
• Experience with modern data storage solutions: Data lakes (Delta tables), and data warehouses.
• Experience with data orchestration tools (Dagster, Airflow).
• Experience with streaming technologies (Kafka, Spark structured streaming).
• Experience with cloud platforms (AWS S3, EC2 etc.)
• OLAP Databases: Hands-on experience with ClickHouse and/or Apache Druid for real-time analytics and low-latency data serving.
• Strong problem-solving skills and ability to excel in a fast-paced startup environment.
• Based in Barcelona or ready to relocate to Barcelona.

Nice to have:

• Experience with Databricks platform.
• Experience in building ML data platforms.