• Lead a team of Engineers, setting clear expectations and providing continuous feedback, coaching, and mentoring to ensure success and growth
• Working closely with feature owners, economy, liveops and other development teams to implement feature simulations and technological pipelines for Monopoly GO!
• Driving the implementation of systems that transform raw game data into analytical datasets for simulation and evaluation
• Ensuring technical performance is “Best-in-Class” throughout development
• Writing automated, high-quality tests (unit, integration, load, etc.) and working with QA teams to improve gameplay experience, curtail exploits and ensure that everything works smoothly
• Reviewing Technical Design Documents and provide feedback and guidance to other engineers
• Collaborating and communicating with cross-functional departments including: economy, liveops, qa, etc.
• Participating in a strong engineering team and culture
• Live game support & troubleshooting
• Contributing to technical plans and discussing the workflows and requirements with stakeholders
• Implementing tools to empower our liveops and game design teams in the creation of new and exciting game-play experiences
• Explore AI-assisted tools (LLMs, copilots, automation frameworks) to improve productivity, enhance analysis depth, and accelerate iteration cycles

• 6+ years as part of a professional game development team or other relevant area
• Experience managing people, driving 1:1s and performance reviews, doing follow ups and providing regular feedback to direct reports
• Experience driving and leading the technical execution of complex and interdisciplinary developments
• Mastery of C#, Python or another OO language, including experience with asynchronous and multi-threaded programming paradigms
• Hands-on experience with cloud computing (AWS, GCP...) and low-latency, high-scale distributed systems
• Strong computer science and engineering fundamentals (data structures, concurrency, design patterns, algorithms)
• Strong understanding of game framework architecture at scale, maintainability over time, robust API design, etc.
• Strong knowledge of application design best patterns and practices; understanding of maintainability concerns when designing and implementing applications
• Enjoy solving complex technical problems, especially in large systems
• Willingness to learn and work with new technologies
• You’re a great tech communicator who knows how to share knowledge with non-technical people
• You have a desire to seek out and take on user feedback to drive world class application development
• A passion for games

• Experience building your own games as personal projects or game jams
• Experience with AWS, Docker, Kibana, Ansible
• Experience with automated testing
• Solid experience with SQL and at least one data warehouse (BigQuery preferred)
• Knowledge of probability, applied statistics, and simulation techniques
• Experience with distributed processing tools: Spark, PySpark, or alternatives
• Experience building ETL/ELT pipelines using Airflow, DBT, or similar frameworks
• Experience in gaming, monetization, or game economy
• Familiarity with gameplay logic or LiveOps systems
• Experience developing internal libraries or tools for non-technical teams
• Curiosity for experimenting with AI systems to extend capabilities of existing pipelines or prototype new evaluation methods

At Scopely, we believe in creating a supportive work environment where everyone is treated with respect and inclusivity. We welcome individuals from all backgrounds and are committed to providing equal employment opportunities regardless of age, race, ethnicity, gender, sexual orientation, religion, disability, or any other protected status.

Highlights

Location: Spain, Remote

Language: Russian-speaking team; English proficiency required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

As a Product Analyst, you will be a critical partner to our business teams, working closely with Sales, Marketing, Customer Success (CSM), and Partnerships. Your core mission is to transform raw data into actionable insights that measure effectiveness, drive strategy, and inform the product roadmap. While our development team is Russian-speaking, our main audience and business stakeholders are in the U.S., making your fluency in English essential for success.

What You’ll Do

• Uncover critical insights by forming hypotheses and validating them with data.
• Identify global and local trends in user behavior to inform product decisions.
• Analyze and interpret customer metrics to measure impact and value.
• Design and evaluate A/B tests with prospective customers to optimize performance.
• Handle ad-hoc analytical requests from stakeholders across the organization.

Requirements

• 4+ years of experience as a Data Analyst or Product Analyst.
• A strong foundation in mathematical statistics and probability theory.
• Advanced proficiency in SQL.
• Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
• Hands-on experience with BI tools (Tableau, Power BI, Metabase).
• Excellent command of written and spoken English (C1 level or higher).
• A proactive, curious mindset with strong analytical and communication skills.

Our Tech Stack

• Languages & Libraries: Python
• Databases: ClickHouse, MongoDB, PostgreSQL
• BI & Visualization: Tableau, Grafana, Metabase
• Orchestration: Airflow
• Version Control: Git

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Location: Spain, Remote

Language: Russian-speaking team; Professional working proficiency in English (B1 or higher)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We’re looking for a Product Analyst to join the Donor Portal (Donor Experience) team. The Donor Portal team owns the post-donation experience – everything that happens after a donor completes a donation. The team focuses on reducing churn and increasing subscription LTV by improving subscription management within the donor portal (pauses, amount changes, skipping charges, etc.), as well as enhancing donor communications via email.

What You’ll Do

• Run A/B tests
• Identify insights in data, conduct research, and help product teams uncover growth opportunities.
• Work with retention rate and subscription/supporter LTV metrics.
• Design and build data marts.
• Develop and maintain BI dashboards.
• Handle ad-hoc requests from product teams.

Requirements

• 5+ years of professional experience as a Data Analyst or Product Analyst.
• A strong foundation in mathematical statistics and probability theory.
• Advanced proficiency in SQL.
• Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
• Hands-on experience with BI tools (Tableau, Power BI, Metabase).
• Strong written English for clear documentation and communication.
• A proactive, detail-oriented mindset with a passion for solving complex problems.

Our Tech Stack

• Languages & Libraries: Python
• Databases: ClickHouse, MongoDB, PostgreSQL
• BI & Visualization: Tableau, Grafana
• Orchestration: Airflow
• Version Control: Git

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Role: Senior ML-Engineer

Location: Spain, Remote

Language: Russian-speaking team; Strong English required (B2)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We're looking for an ML Engineer with 5+ years of production experience to strengthen our ML team. We operate as an internal service and centre of excellence for 10+ product teams at Fundraise Up. This means you won't be tied to a single feature: one day you might be optimising donation amounts and upsell offers, and the next you could be building a smart assistant for the admin panel or working on transaction classification.

We actively use not only classical ML, but also RL, and we're expanding our LLM-based solutions — prompt engineering and pipeline design with LLM APIs (OpenAI and equivalents). That's why we're looking for someone with a broad mindset who isn't afraid to experiment and can choose the most effective approach for each task.

The project's main audience and business team are based in the US. Although the product development team is Russian-speaking, you may occasionally need to write in English.

What You’ll Do

• Develop and deploy ML solutions across different business areas using tabular data (uplift models, recommender systems). We are also actively developing projects that will involve e-commerce mechanics.
• Select the most appropriate ML/LLM approaches or propose alternative solutions.
• Build end-to-end ML solutions: data preparation, training, API development, and monitoring.
• Design prompts and LLM API-based pipelines for specific product tasks: classification, content generation, and response quality evaluation.

Requirements

• 5+ years of ML/DS experience solving real product problems
• Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting); NLP knowledge is a plus
• Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (CR, LTV)
• Strong engineering culture: confident in Python with a product-oriented approach to development; we value clean code, knowledge of design patterns, and solid engineering practices
• Data skills: advanced SQL; ability to independently and efficiently build complex datasets in ClickHouse and work with MongoDB
• MLOps understanding: hands-on experience with experiment tracking tools and understanding of production workflows (Docker, Git, CI/CD)
• Autonomy: ability to break down problems, choose the right tech stack (or justify a non-ML solution), and deliver to production

Our Tech Stack

Core: Python (uv, ruff), FastAPI, Pydantic, Docker

Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)

Data: ClickHouse, MongoDB, pandas, Polars, Redis

MLOps: MLflow, Airflow

Monitoring: Grafana, Sentry

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Spain, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We're looking for an ML Engineer with 5+ years of production experience to own a high-impact client intelligence initiative. Following a successful proof-of-concept with an external consultant, we are bringing this project fully in-house. The ultimate goal is to generate a comprehensive, enriched list of all potential clients globally — understanding their product requirements, industry verticals, and overall revenue potential — and deploy a scoring model that feeds directly into our sales pipeline.

This is an end-to-end ownership role. You will build from the ground up: data collection, enrichment, modeling, and production deployment. The project is co-managed by company executives and has a high strategic value.

What You’ll Do

• Build a market intelligence data-base via collecting different types of data (scraping, enrichment), fixing data pipeline and creating an ML model for scoring and analysis of the raw data.
• Design and operate scrapers to extract key signals from nonprofit websites, including products used, payment tools, and industry vertical indicators.
• Develop critical filters such as an "Is this website for fundraising?" binary classifier, alongside other features that distinguish high-potential prospects.
• Source and integrate financial data from international nonprofit registries, as well as third-party signals from SimilarWeb and Facebook.
• Store and structure the enriched dataset in our internal database, making it accessible and useful across the broader team for research and analysis.
• Work closely with the sales team to understand their qualification criteria. Analyze disqualified accounts in Salesforce to identify common exclusion patterns and refine scoring accordingly.
• Deploy the scoring model and own the process of integrating outputs into Salesforce in a clean, maintainable way.
• Build a scraper to monitor existing clients' websites, tracking whether Fundraise Up tools are correctly implemented across their properties.

Challenges You'll Navigate

• At the scale of ~1 million domains, expect domain duplicates, inconsistent data, and significant noise. You'll need to develop robust, cost-efficient filtering pipelines.
• A single model won't cover everything — you'll likely build several targeted sub-models tailored to specific verticals and geographies as the project matures.
• All of this needs to be accomplished without incurring high infrastructure or data costs. Pragmatic, scrappy solutions are valued here.

Requirements

• 5+ years of ML/DS experience solving real product problems
• Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting) and understanding of modern NLP/LLM approaches
• Proven experience with large-scale web scraping and data pipeline construction
• Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (conversion rate, LTV)
• Strong engineering culture: confident in Python with a product-oriented approach; we value clean code, knowledge of design patterns, and solid engineering practices
• Advanced SQL; ability to independently build complex datasets in ClickHouse and work with MongoDB
• MLOps understanding: hands-on experience with experiment tracking and production workflows (Docker, Git, CI/CD)
• Autonomy: ability to break down ambiguous problems, choose the right tech stack, and deliver to production

Our Tech Stack

Core: Python (uv, ruff), FastAPI, Pydantic, Docker

Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)

Data: ClickHouse, MongoDB, pandas, Polars, Redis

MLOps: MLflow, Airflow

Monitoring: Grafana, Sentry

Infra: linux server admin, distributed computation

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights

Location: Remote (CET hours preferred)

Compensation: €5,200 - €6,100 gross + stock options

Language: Russian-speaking team, English B1+ required

About Fundraise Up

We’re Fundraise Up - a global fundraising platform built to make donating to nonprofits fast, seamless, and accessible to all. Every month, our technology powers tens of millions of dollars in donations across the globe. We focus on innovation that directly impacts results: faster load times, higher conversion rates, global payment support, and accessibility-first design.

Our platform is trusted by many of the world’s leading nonprofits, including UNICEF, the Alzheimer’s Association, and a wide range of global NGOs. With a 4.9/5 rating across top software review platforms, we’re recognized not just for our impact - but for the quality of the product we deliver.

A Truly Global Product

We operate in the enterprise segment, serving nonprofit organizations across North America, the United Kingdom, Australia, and Europe.

We’re building a large and complex product ecosystem that serves nonprofits, donors, and partners around the world. The platform includes a modern checkout experience and customizable widgets (each a standalone SPA), donor, organization, and partner portals, admin tools, and several internal apps.

Our backend is powered by Node.js (Koa, NestJS) and MongoDB. The frontend stack includes Webpack, Vue.js, and React, with nearly all code written in TypeScript. For high-throughput messaging and background processing, we use Kafka (for millions of events) and Bull (Redis). Analytics data is stored in ClickHouse, and we use Elasticsearch for search.

The Team

We are a distributed team of 160+ product professionals, including 80+ engineers. Our team members are mainly based across Spain, Poland, Portugal, Georgia, Armenia, Serbia, Turkey, and Cyprus. Many of our developers bring 5 - 10+ years of experience, and we foster a culture of deep technical curiosity and knowledge sharing.

Despite our scale, we operate like a focused team - where every task matters and every voice is heard. We value thoughtful collaboration, strong engineering practices, and a product mindset. You’ll be joining a team where quality, mentorship, and mutual respect come first.

About the Role

As a Senior Data Engineer, you will be responsible for designing, building, and optimizing scalable data pipelines and ETL/ELT processes.

At the initial stage, you will be the first engineer in this direction, taking full ownership of the data domain. As the product and data needs grow, we plan to expand the team, and you will have the opportunity to contribute to its development.

This role requires a high level of autonomy and ownership, combined with close collaboration with analytics, Data Science, and engineering teams.

What You’ll Do

• Design and evolve the architecture of the data platform and storage systems.
• Build reliable ETL/ELT processes and develop scalable data pipelines for delivering data into a centralized analytical warehouse.
• Maintain and further develop the Data Warehouse.
• Collaborate with engineering and analytics teams on system design and architectural decisions.
• Ensure data governance and maintain high standards of data quality.
• Write and optimize queries for MongoDB and ClickHouse.
• Manage and maintain workflows in Airflow.

Requirements

• Experience: 7+ years of experience as a Data Engineer.
• Programming: 5+ years of experience with Python, TypeScript, Node.js, Kafka.
• Strong understanding of data processing algorithms and principles.
• Hands-on experience with ClickHouse, Airflow, Amazon S3, Git, Docker.
• Solid understanding of Data Lake and Data Warehouse architectures.
• Experience working with large-scale data and query optimization.
• Ability to work collaboratively toward shared goals.
• Strong sense of ownership, responsibility, and proactivity.
• English level: B1+.

Nice to Have

• Experience with Apache Parquet, MLflow, MongoDB. 

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses.
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Location: Spain, Remote

Language: Russian-speaking team; Professional working proficiency in English (B1 or higher)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

As a Product Analyst, you will be a versatile data expert at the heart of our product decisions. Your work will span the full analytical lifecycle—from building data marts and ETL processes to designing and analyzing A/B tests and delivering key insights to stakeholders. This is a role for a proactive analyst who is comfortable working across a wide range of tasks and is passionate about using data to find the truth and drive results.

What You’ll Do

• Uncover Actionable Insights: Identify key trends in user behavior, develop data-backed product hypotheses, and work with teams to test them.
• Own A/B Testing: Design, launch, and analyze A/B tests to validate ideas and optimize product performance.
• Build a Data Foundation: Create and maintain data marts and BI reports to visualize product and operational metrics for the entire company.
• Perform Deep-Dive Analyses: Handle ad-hoc analytical requests to answer critical business and product questions.

Requirements

• 5+ years of professional experience as a Data Analyst or Product Analyst.
• A strong foundation in mathematical statistics and probability theory.
• Advanced proficiency in SQL.
• Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
• Hands-on experience with BI tools (Tableau, Power BI, Metabase).
• Strong written English for clear documentation and communication.
• A proactive, detail-oriented mindset with a passion for solving complex problems.

Our Tech Stack

• Languages & Libraries: Python
• Databases: ClickHouse, MongoDB, PostgreSQL
• BI & Visualization: Tableau, Grafana
• Orchestration: Airflow
• Version Control: Git

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Location: Spain, Remote

Language: Russian-speaking team; Professional working proficiency in English (B1 or higher)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We’re looking for a Team Lead to join our Product Analytics team for the New Products direction. The New Products direction is our “internal incubator,” responsible for the company’s future revenue. We don’t just improve existing products — we launch entirely new business verticals from scratch.

Currently, we have three key focus areas:
    1.    P2P (Peer-to-Peer): Building tools for mass fundraising events and marathons (a market with $8M+ ARR potential).
    2.    Tap-to-Pay & Kiosks: Enabling offline donations via smartphones and physical terminals.
    3.    Major Donors: Leveraging AI to identify and engage high-value donors.

At the moment, the team consists of one analyst who has already started working on the P2P product.

What You’ll Do

• Act as a right hand to product leads (PMs): help define success criteria for pilots and evaluate whether new products gain traction
• Build analytics from scratch: design data collection systems and ensure reliability monitoring from day one
• Evaluate the performance of new product launches
• Lead and grow the team: mentor team members, run 1:1s, and establish processes in a fast-growing function, as well as plan the roadmap and oversee execution and timelines

Requirements

• 5+ years of experience as a Product Analyst
• 2+ years of team management experience
• Strong knowledge of mathematical statistics and probability theory
• Proficiency in Python (NumPy, pandas, matplotlib, seaborn, scikit-learn)
• Advanced SQL skills
• Experience with BI tools (Tableau, Power BI, Metabase)

Our Tech Stack

• Python
• ClickHouse, MongoDB, PostgreSQL
• Tableau, Grafana
• Airflow
• Git

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• 31 days off
• 100% paid telemedicine plan
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Co-working
• Remote working
• Relocation package

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Scopely is seeking a highly motivated Senior Analytics Engineer to join our Strategy & Business Operations team in Barcelona on a 2 day a week hybrid basis! 

At Scopely, we care deeply about what we do and want to inspire play every day - whether in our work environments alongside our talented colleagues or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing, and innovating the mobile games industry, connecting millions of people worldwide daily.  

The Strategy and Business Operations team works closely with the Senior Leadership of Scopely to answer critical business-related questions. By acting as a strategic partner, the team translates complex data into actionable insights that drive the company's decision-making process and long-term growth.

What You’ll Do  

• Lead and collaborate with engineers, product teams, and analysts to develop self-serve insight products that are responsive, precise, and scalable at petabyte levels
• Oversee the entire data product lifecycle, including designing new tracking plans, developing data models, ELT pipelines, and self-serve insight products like Looker explores and dashboards
• Act as a guardian of data quality, ensuring consistent metric reporting across a wide range of data products
• Utilize cutting-edge technology stack including BigQuery, dbt and Looker
• Provide technical leadership and partner with our stakeholders and their teams to enhance their daily operations and product success.
• Bring expertise in a specific part of the data stack and lifecycle while contributing broadly across all aspects
• Mentor team members and drive the adoption of best practices within the team

What We’re Looking For  

• A strong passion for solving complex analytical puzzles
• Proven ability to translate business needs into advanced analytics solutions
• Deep expertise with the modern data stack (BigQuery, Snowflake, dbt, Looker, Airflow, GitHub, Terraform, command line-based workflows)
• Exceptional SQL skills coupled with at least 5 years of relevant experience in data analytics or engineering roles
• Demonstrate a solid proficiency in Python, with the ability to write clean, maintainable scripts to automate data workflows, perform exploratory data analysis and integrate various data sources within our modern tech stack.
• Solid understanding of data modeling principles (e.g., Kimball methodology, star schemas)
• A high valuation of business context and the drive to achieve technical excellence
• An inclination towards collaboration and pride in contributing to high-functioning teams
• Enjoyment in working within fast-paced, growth-oriented environments
• A sense of fun at work, with extracurricular interests like Ping Pong or Mario Kart seen as a bonus!

At Scopely, we create games for everyone - and want to ensure that the people behind our games reflect that!   We are committed to creating a diverse, supportive work environment where everyone is treated with respect. We are committed to providing equal employment opportunities and welcome individuals from all backgrounds to join us & embrace the adventure!  

Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.

This role will have access to sensitive and/or confidential employee or customer personally identifiable information (PII) and/or Company financial information, and therefore will be subject to background checks upon receiving a conditional offer of employment.    

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!

Job details
● 💼 Engineering Team
● 📍 Spain - Barcelona
● 🕜 Full-Time/Remote

What you will do

As a Data Engineer in our new Data Products team, you will play a key role in shaping the quality and business value of our core data assets. You will be hands-on in designing, building, and maintaining the data pipelines that serve teams across Lighthouse. You will act as a bridge between our data and the business, collaborating with stakeholders and ensuring our data effectively enables its consumers.

Where you will have impact

• Become the expert for key data products, understanding the full data lifecycle, quality, and business applications.
• Design, implement, and maintain the streaming and batch data pipelines that power our products and internal analytics.
• Collaborate directly with data consumers to understand their needs, gather requirements, and deliver data solutions.
• Deliver improvements in data quality, latency, and reliability.
• Show a product engineering mindset, focusing on delivering value and solving business problems through data.
• You will be at the forefront of our AI evolution, helping to embed intelligence into our platform. You’ll not only build AI features for our customers but also champion an AI-first development culture within the engineering team.
• Mentor other engineers, sharing your expertise and contributing to their growth.

About our team

The Data Products Team is the definitive source of truth for Lighthouse's data, sitting at the foundational layer of our entire data ecosystem.

Their core mission is to model and deliver high-quality, foundational data products that are essential ingredients for all downstream product features, machine learning models, and data science initiatives across the company:

• Data Modeling & Ownership: Defining and optimizing core data entities for product and analytical use.
• Pipeline Engineering: Building robust ETL/ELT pipelines to transform raw integrated data into trusted domains.
• Data Quality: Establishing standards and monitoring the health of all foundational data assets. 

We are the core of the Lighthouse platform. We take ingested data from our Integrations teams, turn it into usable data products, and provide that clean output to both the Product Engineering and Data Science & Analytics teams. We rely on the Data Platform team for infrastructure support and tooling.

What's in it for you?

• Flexible time off: Autonomy to manage your work-life balance.
• Alan Flex benefits: 160€/month for food or nursery.
• Flexible retribution: Optional benefits through tax-free payroll deductions for food, transportation and/or nursery. 
• Wellbeing support: Subsidized ClassPass subscription.
• Comprehensive health insurance: 100% Alan coverage for you, your spouse, and dependents.
• Impactful work: Shape products relied on by 85,000+ users worldwide.
• Referral bonuses: Earn rewards for bringing in new talent.

Who you are

• Experience in a data engineering role, with a proven track record of building scalable data pipelines.
• A product engineering mindset, with a focus on understanding business context and stakeholder needs.
• Professional proficiency in Python for data processing and pipeline development.
• Strong knowledge of cloud database solutions such as BigQuery, Snowflake, or Databricks.
• You are a forward-thinking builder who views AI as a core component of modern architecture. You have a proven interest (or experience) in working with LLMs, agentic workflows, or AI-assisted coding tools to ship higher-quality code, faster.
• Excellent communication and stakeholder management skills.

We welcome

• Experience with microservice architectures and data streaming systems like Kafka or Google Cloud Pub/Sub.
• Familiarity with data governance or data quality tools such as Atlan or Soda.
• Experience mentoring other engineers.

Technologies you will work with

Mostly, but not limited to: GCP, Python, BigQuery, Kubernetes, Airflow, dbt, Terraform, Atlan (data governance tool), Soda.

Job details
● 💼 Engineering Team
● 📍 Spain
● 🕜 Full-Time/Remote

What you will do

As a Senior Data Engineer in our new Data Products team, you will play a key role in shaping the quality and business value of our core data assets. You will be hands-on in designing, building, and maintaining the data pipelines that serve teams across Lighthouse. You will act as a bridge between our data and the business, collaborating with stakeholders and ensuring our data effectively enables its consumers.

Where you will have impact

• Become the expert for key data products, understanding the full data lifecycle, quality, and business applications.
• Design, implement, and maintain the streaming and batch data pipelines that power our products and internal analytics.
• Collaborate directly with data consumers to understand their needs, gather requirements, and deliver data solutions.
• Deliver improvements in data quality, latency, and reliability.
• Show a product engineering mindset, focusing on delivering value and solving business problems through data.
• You will be at the forefront of our AI evolution, helping to embed intelligence into our platform. You’ll not only build AI features for our customers but also champion an AI-first development culture within the engineering team.
• Mentor other engineers, sharing your expertise and contributing to their growth.

About our team

The Data Products Team is the definitive source of truth for Lighthouse's data, sitting at the foundational layer of our entire data ecosystem.

Their core mission is to model and deliver high-quality, foundational data products that are essential ingredients for all downstream product features, machine learning models, and data science initiatives across the company:

• Data Modeling & Ownership: Defining and optimizing core data entities for product and analytical use.
• Pipeline Engineering: Building robust ETL/ELT pipelines to transform raw integrated data into trusted domains.
• Data Quality: Establishing standards and monitoring the health of all foundational data assets. 

We are the core of the Lighthouse platform. We take ingested data from our Integrations teams, turn it into usable data products, and provide that clean output to both the Product Engineering and Data Science & Analytics teams. We rely on the Data Platform team for infrastructure support and tooling.

What's in it for you?

• Flexible time off: Autonomy to manage your work-life balance.
• Alan Flex benefits: 160€/month for food or nursery.
• Flexible retribution: Optional benefits through tax-free payroll deductions for food, transportation and/or nursery. 
• Wellbeing support: Subsidized ClassPass subscription.
• Comprehensive health insurance: 100% Alan coverage for you, your spouse, and dependents.
• Impactful work: Shape products relied on by 85,000+ users worldwide.
• Referral bonuses: Earn rewards for bringing in new talent.

Who you are

• Experience in a data engineering role, with a proven track record of building scalable data pipelines.
• A product engineering mindset, with a focus on understanding business context and stakeholder needs.
• Professional proficiency in Python for data processing and pipeline development.
• Strong knowledge of cloud database solutions such as BigQuery, Snowflake, or Databricks.
• You are a forward-thinking builder who views AI as a core component of modern architecture. You have a proven interest (or experience) in working with LLMs, agentic workflows, or AI-assisted coding tools to ship higher-quality code, faster.
• Excellent communication and stakeholder management skills.

We welcome

• Experience with microservice architectures and data streaming systems like Kafka or Google Cloud Pub/Sub.
• Familiarity with data governance or data quality tools such as Atlan or Soda.
• Experience mentoring other engineers.

Technologies you will work with

Mostly, but not limited to: GCP, Python, BigQuery, Kubernetes, Airflow, dbt, Terraform, Atlan (data governance tool), Soda.

Type: Contract, per-project.
Location: Remote — within LATAM with ET ±1 hour
Availability: Contractor (40 hours per week)

Job Title: Data / Platform Engineer (AWS & Data Pipelines)

We are looking for a highly motivated Data / Platform Engineer to join our team and help design, build and operate scalable data pipelines and cloud-based solutions.

In this role, you will work closely with engineering and product teams to build both streaming and batch data pipelines, contribute to system design, and help drive automation and monitoring across our data platform.

Key Responsibilities

• Design, build, maintain and primarily operate scalable streaming and batch data pipelines, with a strong focus on maintenance, monitoring, troubleshooting and continuous improvement of existing pipelines.

• Work with AWS services, including Redshift, EMR and ECS, to support data processing and analytics workloads.

• Develop and maintain data workflows using Python and SQL.

• Orchestrate and monitor pipelines using Apache Airflow.

• Build and deploy containerized applications using Docker and Kubernetes.

• Break down high-level system designs into well-defined, deliverable tasks with realistic estimates.

• Collaborate with cross-functional teams in a fast-paced and distributed environment across the US and Europe.

• Drive automation, observability and monitoring to improve reliability, performance and operational efficiency.

• Support knowledge transfer and ownership handover as part of the planned transition to the consuming team.

Required Qualifications

• Strong professional experience with Python and SQL.

• Hands-on experience with AWS, specifically Redshift, EMR and ECS. AWS experience is mandatory (other cloud providers are not considered equivalent for this role).

• Proven experience building and operating both streaming and batch data pipelines.

• Professional experience with Apache Airflow, Docker and Kubernetes.

• Ability to translate high-level system designs into actionable technical tasks and realistic estimates.

• Comfortable working in dynamic and fast-paced environments and in distributed teams.

• Strong interest in automation and monitoring.

• Strong hands-on experience with Apache Spark.

• Senior-level profile with strong autonomy, communication skills and ability to work effectively in distributed teams.

• Proven ability to transfer knowledge and support ownership handovers.

• Fluent or professional working proficiency in English (both written and spoken).

Nice to Have

• Previous experience in the telecom industry.

• Experience with machine learning systems and/or event-driven architectures.

• Experience with Apache Iceberg.
  
  (*) SOUTHWORKS only hires individuals from countries that are not blocked or sanctioned by the United States, including those identified on the United States Office of Foreign Asset Control (OFAC).

Rithum™ is the world’s most trusted commerce network, accelerating how brands, suppliers, and retailers work together to deliver seamless e-commerce experiences. We provide an unmatched platform for brands and retailers, enabling them to accelerate growth, optimise operations across channels, scale product offerings and enhance margins.

Today, more than 40,000 companies trust Rithum to grow their business across hundreds of channels, representing over $50 billion in annual GMV. Using our commerce, marketing, and delivery solutions, our customers create optimised consumer shopping journeys from beginning to end.

Overview

As a Senior Data Engineer, you are a key architect in developing, delivering and maintaining intelligent data infrastructure that powers advanced analytics. You are an experienced data engineer with strong ETL pipeline and dimensional modeling skills, who is ready to leverage AI as a powerful collaborator and brings a depth of knowledge to ensure it is employed effectively for the long-term health of our business systems. You are responsible for building complex data pipelines from the ground up, delivering data into and enhancing a database infrastructure that powers advanced analytics, AI-driven decision-making, and autonomous data operations. You work across the organization, supporting and collaborating with our product teams, engineers, data scientists, and data analysts. In this context, you enhance and support our company’s cloud data architecture to support our products and data initiatives, for external clients as well as internal users.

Responsibilities

Core Data Infrastructure 

• Design and implement scalable ETL/ELT workflows that support both batch and streaming data using AWS primitives (e.g., S3, Kinesis, Glue, Redshift, Athena) 
• Architect and maintain cloud-native data platforms with automated ingestion, transformation, and governance pipelines using modern tools like DBT, Apache Spark, Delta Lake, Airflow, and Databricks 
• Work with stakeholders, including the Product, BI, and Support teams, to assist with data-related technical challenges and support their data and infrastructure needs.
• Collaborate with cross-functional Engineering teams using analytics to predict data needs and proactively deliver solutions. 
• Assist in the optimization of data lake/lakehouse infrastructure, to support AI workloads and large-scale analytics. 

Governance & Collaboration 

• Ensure data quality, lineage, and observability.
• Develop and enforce data governance policies, including compliance monitoring and privacy protection. 
• Partner with Data Scientists to optimize data pipelines for model training, inference, and continuous learning workflows. 

Advanced Data Operations 

• Build self-healing data pipelines with AI-driven error detection, root cause analysis, and automated remediation capabilities. 
• Implement intelligent data lineage tracking to automatically discover relationships between datasets and predict downstream impact of changes. 
• Create AI-assisted data discovery systems that help stakeholders find relevant datasets and understand data semantics through natural language interfaces. 
• Participate in on-call rotation, as needed.

AI-Enhanced Development

• Leverage AI coding assistants (GitHub Copilot, Cursor, etc.) to
• Accelerate development cycles, generate complex SQL queries, and automatically optimize data pipeline code. 
• Develop data quality monitoring, using anomaly detection and data profiling tools to identify issues, before they impact downstream systems. 
• Optimize pipeline orchestration, with ML to predict optimal scheduling, resource allocation, and failure recovery patterns.
• Generate and maintain living documentation that evolves with code changes. 

Leadership & Innovation 

• Participate in the full software development lifecycle, including both manual and AI-assisted requirements gathering, automated testing, and intelligent deployment strategies. 
• Mentor junior engineers on both traditional data engineering practices and effective use of AI development tools. 
• Lead tool evaluation and adoption for the data engineering team, establishing best practices for human-AI collaboration. 
• Drive innovation in data architecture by experimenting with emerging technologies.

Qualifications 

Minimum Qualifications  

• 3+ years of experience in data engineering, including building and maintaining large-scale data pipelines
• Extensive experience in SQL RDBMS (SQLServer or similar) with dimensional modeling using star schema, and foundational data warehousing concepts
• Hands-on experience with AWS services such as Redshift, Athena, S3, Kinesis, Lambda, Glue 
• Experience with DBT, Databricks or similar data platform tooling
• Experience working with structured and unstructured data and implementing data quality frameworks
• Excellent communication and collaboration skills 
• Demonstrated experience using AI coding tools (GitHub Copilot, Cursor, or similar), with understanding of prompt engineering, to enhance development productivity 
• Understanding of AI/ML concepts and data requirements, including feature stores, model versioning, and real-time inference pipelines

Preferred Qualifications 

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Experience in a SaaS or e-commerce environment with AI/ML products
• Knowledge of stream processing frameworks like Kafka, Flink, or Spark Structured Streaming 
• Familiarity with LLMOps and AI model deployment patterns in data infrastructure 
• Experience with AI-powered data tools such as automated data catalogs, intelligent monitoring systems, or AI-assisted query optimization
• Proven ability to thrive in a fast-paced, agile environment with shifting priorities and emerging technologies
• Experience with containerization and orchestration tools like Docker and Kubernetes 

Travel Required

Up to 10%

Other Duties

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

What it’s like to work at Rithum 

When you join Rithum, you can expect to work with smart risk-takers, courageous collaborators, and curious minds.

As part of the Rithum team, you are valued, supported, and included. Guided by a transparent culture and accessible, approachable leadership, we offer career opportunities aligned to your ambitions and talents. To ensure work and life balance works for you, we also offer an array of resources to support you and your families, including comprehensive benefits and wellness plans.

At Rithum you will:

• Partner with the leading brands and retailers.
• Connect with passionate professionals who will help support your goals.
• Participate in an inclusive, welcoming work atmosphere.
• Achieve work-life balance through remote-first working conditions, generous time off, and wellness days.
• Receive industry-competitive compensation and total rewards benefits.

Benefits 

• Medical coverage provided through Irish Life Health; premiums paid by the company 
• Life & disability insurance
• Pension plan with 5% company match
• Competitive time off package with 25 Days of PTO, 11 Company-paid holidays, 2 Wellness days and 1 Paid Volunteer Day 
• Access to tools to support your wellbeing such as the Calm App and an Employee Assistance Program 
• €50/month Remote work stipend for internet
• Professional development stipend and learning and development offerings to help you build the skills and connections you need to move forward in your career. 
• Charitable contribution match per team member  

Rithum is an equal opportunity employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates without regard to race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other protected characteristic. All employment is decided on the basis of qualifications, merit, and business need.

We're committed to providing reasonable accommodations in accordance with the law for qualified applicants. If you require assistance during the interview process due to a medical condition or need support accessing our website or completing the application process, please reach out to us by completing the Accommodations Request Form. Your comfort and accessibility are important to us, and we're here to ensure a seamless experience as you explore opportunities with our team.

Rithum™ is the world’s most trusted commerce network, accelerating how brands, suppliers, and retailers work together to deliver seamless e-commerce experiences. We provide an unmatched platform for brands and retailers, enabling them to accelerate growth, optimise operations across channels, scale product offerings and enhance margins.

Today, more than 40,000 companies trust Rithum to grow their business across hundreds of channels, representing over $50 billion in annual GMV. Using our commerce, marketing, and delivery solutions, our customers create optimised consumer shopping journeys from beginning to end.

Overview

As a Senior Data Engineer, you are a key architect in developing, delivering and maintaining intelligent data infrastructure that powers advanced analytics. You are an experienced data engineer with strong ETL pipeline and dimensional modeling skills, who is ready to leverage AI as a powerful collaborator and brings a depth of knowledge to ensure it is employed effectively for the long-term health of our business systems. You are responsible for building complex data pipelines from the ground up, delivering data into and enhancing a database infrastructure that powers advanced analytics, AI-driven decision-making, and autonomous data operations. You work across the organization, supporting and collaborating with our product teams, engineers, data scientists, and data analysts. In this context, you enhance and support our company’s cloud data architecture to support our products and data initiatives, for external clients as well as internal users.

Responsibilities

Core Data Infrastructure 

• Design and implement scalable ETL/ELT workflows that support both batch and streaming data using AWS primitives (e.g., S3, Kinesis, Glue, Redshift, Athena) 
• Architect and maintain cloud-native data platforms with automated ingestion, transformation, and governance pipelines using modern tools like DBT, Apache Spark, Delta Lake, Airflow, and Databricks 
• Work with stakeholders, including the Product, BI, and Support teams, to assist with data-related technical challenges and support their data and infrastructure needs.
• Collaborate with cross-functional Engineering teams using analytics to predict data needs and proactively deliver solutions. 
• Assist in the optimization of data lake/lakehouse infrastructure, to support AI workloads and large-scale analytics. 

Governance & Collaboration 

• Ensure data quality, lineage, and observability.
• Develop and enforce data governance policies, including compliance monitoring and privacy protection. 
• Partner with Data Scientists to optimize data pipelines for model training, inference, and continuous learning workflows. 

Advanced Data Operations 

• Build self-healing data pipelines with AI-driven error detection, root cause analysis, and automated remediation capabilities. 
• Implement intelligent data lineage tracking to automatically discover relationships between datasets and predict downstream impact of changes. 
• Create AI-assisted data discovery systems that help stakeholders find relevant datasets and understand data semantics through natural language interfaces. 
• Participate in on-call rotation, as needed.

AI-Enhanced Development

• Leverage AI coding assistants (GitHub Copilot, Cursor, etc.) to
• Accelerate development cycles, generate complex SQL queries, and automatically optimize data pipeline code. 
• Develop data quality monitoring, using anomaly detection and data profiling tools to identify issues, before they impact downstream systems. 
• Optimize pipeline orchestration, with ML to predict optimal scheduling, resource allocation, and failure recovery patterns.
• Generate and maintain living documentation that evolves with code changes. 

Leadership & Innovation 

• Participate in the full software development lifecycle, including both manual and AI-assisted requirements gathering, automated testing, and intelligent deployment strategies. 
• Mentor junior engineers on both traditional data engineering practices and effective use of AI development tools. 
• Lead tool evaluation and adoption for the data engineering team, establishing best practices for human-AI collaboration. 
• Drive innovation in data architecture by experimenting with emerging technologies.

Qualifications 

Minimum Qualifications  

• 3+ years of experience in data engineering, including building and maintaining large-scale data pipelines
• Extensive experience in SQL RDBMS (SQLServer or similar) with dimensional modeling using star schema, and foundational data warehousing concepts
• Hands-on experience with AWS services such as Redshift, Athena, S3, Kinesis, Lambda, Glue 
• Experience with DBT, Databricks or similar data platform tooling
• Experience working with structured and unstructured data and implementing data quality frameworks
• Excellent communication and collaboration skills 
• Demonstrated experience using AI coding tools (GitHub Copilot, Cursor, or similar), with understanding of prompt engineering, to enhance development productivity 
• Understanding of AI/ML concepts and data requirements, including feature stores, model versioning, and real-time inference pipelines

Preferred Qualifications 

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Experience in a SaaS or e-commerce environment with AI/ML products
• Knowledge of stream processing frameworks like Kafka, Flink, or Spark Structured Streaming 
• Familiarity with LLMOps and AI model deployment patterns in data infrastructure 
• Experience with AI-powered data tools such as automated data catalogs, intelligent monitoring systems, or AI-assisted query optimization
• Proven ability to thrive in a fast-paced, agile environment with shifting priorities and emerging technologies
• Experience with containerization and orchestration tools like Docker and Kubernetes 

Travel Required

Up to 10%

Other Duties

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

What it’s like to work at Rithum 

When you join Rithum, you can expect to work with smart risk-takers, courageous collaborators, and curious minds.

As part of the Rithum team, you are valued, supported, and included. Guided by a transparent culture and accessible, approachable leadership, we offer career opportunities aligned to your ambitions and talents. To ensure work and life balance works for you, we also offer an array of resources to support you and your families, including comprehensive benefits and wellness plans.

At Rithum you will:

• Partner with the leading brands and retailers.
• Connect with passionate professionals who will help support your goals.
• Participate in an inclusive, welcoming work atmosphere.
• Achieve work-life balance through remote-first working conditions, generous time off, and wellness days.
• Receive industry-competitive compensation and total rewards benefits.

Benefits 

• Medical, Dental and Psychology benefits 
• Life insurance and disability benefits
• Competitive time off package with 25 Days of PTO, 8 Company-paid Holidays, 5 paid floating holidays (new in 2026!), 2 Wellness days and 1 Paid Volunteer Day 
• Voucher program for Transportation, Meals & Childcare 
• Remote Working Stipend: €40/month automatically applied in payroll
• Access to tools to support your wellbeing such as the Calm App and an Employee Assistance Program 
• Professional development stipend and learning and development offerings to help you build the skills and connections you need to move forward in your career. 
• Charitable contribution match per team member 

Rithum is an equal opportunity employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates without regard to race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other protected characteristic. All employment is decided on the basis of qualifications, merit, and business need.

We're committed to providing reasonable accommodations in accordance with the law for qualified applicants. If you require assistance during the interview process due to a medical condition or need support accessing our website or completing the application process, please reach out to us by completing the Accommodations Request Form. Your comfort and accessibility are important to us, and we're here to ensure a seamless experience as you explore opportunities with our team.

Rithum™ is the world’s most trusted commerce network, accelerating how brands, suppliers, and retailers work together to deliver seamless e-commerce experiences. We provide an unmatched platform for brands and retailers, enabling them to accelerate growth, optimise operations across channels, scale product offerings and enhance margins.

Today, more than 40,000 companies trust Rithum to grow their business across hundreds of channels, representing over $50 billion in annual GMV. Using our commerce, marketing, and delivery solutions, our customers create optimised consumer shopping journeys from beginning to end.

Overview

As a Senior Data Engineer, you are a key architect in developing, delivering and maintaining intelligent data infrastructure that powers advanced analytics. You are an experienced data engineer with strong ETL pipeline and dimensional modeling skills, who is ready to leverage AI as a powerful collaborator and brings a depth of knowledge to ensure it is employed effectively for the long-term health of our business systems. You are responsible for building complex data pipelines from the ground up, delivering data into and enhancing a database infrastructure that powers advanced analytics, AI-driven decision-making, and autonomous data operations. You work across the organization, supporting and collaborating with our product teams, engineers, data scientists, and data analysts. In this context, you enhance and support our company’s cloud data architecture to support our products and data initiatives, for external clients as well as internal users.

Responsibilities

Core Data Infrastructure 

• Design and implement scalable ETL/ELT workflows that support both batch and streaming data using AWS primitives (e.g., S3, Kinesis, Glue, Redshift, Athena) 
• Architect and maintain cloud-native data platforms with automated ingestion, transformation, and governance pipelines using modern tools like DBT, Apache Spark, Delta Lake, Airflow, and Databricks 
• Work with stakeholders, including the Product, BI, and Support teams, to assist with data-related technical challenges and support their data and infrastructure needs.
• Collaborate with cross-functional Engineering teams using analytics to predict data needs and proactively deliver solutions. 
• Assist in the optimization of data lake/lakehouse infrastructure, to support AI workloads and large-scale analytics. 

Governance & Collaboration 

• Ensure data quality, lineage, and observability.
• Develop and enforce data governance policies, including compliance monitoring and privacy protection. 
• Partner with Data Scientists to optimize data pipelines for model training, inference, and continuous learning workflows. 

Advanced Data Operations 

• Build self-healing data pipelines with AI-driven error detection, root cause analysis, and automated remediation capabilities. 
• Implement intelligent data lineage tracking to automatically discover relationships between datasets and predict downstream impact of changes. 
• Create AI-assisted data discovery systems that help stakeholders find relevant datasets and understand data semantics through natural language interfaces. 
• Participate in on-call rotation, as needed.

AI-Enhanced Development

• Leverage AI coding assistants (GitHub Copilot, Cursor, etc.) to
• Accelerate development cycles, generate complex SQL queries, and automatically optimize data pipeline code. 
• Develop data quality monitoring, using anomaly detection and data profiling tools to identify issues, before they impact downstream systems. 
• Optimize pipeline orchestration, with ML to predict optimal scheduling, resource allocation, and failure recovery patterns.
• Generate and maintain living documentation that evolves with code changes. 

Leadership & Innovation 

• Participate in the full software development lifecycle, including both manual and AI-assisted requirements gathering, automated testing, and intelligent deployment strategies. 
• Mentor junior engineers on both traditional data engineering practices and effective use of AI development tools. 
• Lead tool evaluation and adoption for the data engineering team, establishing best practices for human-AI collaboration. 
• Drive innovation in data architecture by experimenting with emerging technologies.

Qualifications 

Minimum Qualifications  

• 3+ years of experience in data engineering, including building and maintaining large-scale data pipelines
• Extensive experience in SQL RDBMS (SQLServer or similar) with dimensional modeling using star schema, and foundational data warehousing concepts
• Hands-on experience with AWS services such as Redshift, Athena, S3, Kinesis, Lambda, Glue 
• Experience with DBT, Databricks or similar data platform tooling
• Experience working with structured and unstructured data and implementing data quality frameworks
• Excellent communication and collaboration skills 
• Demonstrated experience using AI coding tools (GitHub Copilot, Cursor, or similar), with understanding of prompt engineering, to enhance development productivity 
• Understanding of AI/ML concepts and data requirements, including feature stores, model versioning, and real-time inference pipelines

Preferred Qualifications 

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Experience in a SaaS or e-commerce environment with AI/ML products
• Knowledge of stream processing frameworks like Kafka, Flink, or Spark Structured Streaming 
• Familiarity with LLMOps and AI model deployment patterns in data infrastructure 
• Experience with AI-powered data tools such as automated data catalogs, intelligent monitoring systems, or AI-assisted query optimization
• Proven ability to thrive in a fast-paced, agile environment with shifting priorities and emerging technologies
• Experience with containerization and orchestration tools like Docker and Kubernetes 

Travel Required

Up to 10%

Other Duties

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

What it’s like to work at Rithum 

When you join Rithum, you can expect to work with smart risk-takers, courageous collaborators, and curious minds.

As part of the Rithum team, you are valued, supported, and included. Guided by a transparent culture and accessible, approachable leadership, we offer career opportunities aligned to your ambitions and talents. To ensure work and life balance works for you, we also offer an array of resources to support you and your families, including comprehensive benefits and wellness plans.

At Rithum you will:

• Partner with the leading brands and retailers.
• Connect with passionate professionals who will help support your goals.
• Participate in an inclusive, welcoming work atmosphere.
• Achieve work-life balance through remote-first working conditions, generous time off, and wellness days.
• Receive industry-competitive compensation and total rewards benefits.

Benefits 

• Medical, Dental and Psychology benefits 
• Life insurance and disability benefits
• Competitive time off package with 25 Days of PTO, 8 Company-paid Holidays, 5 paid floating holidays (new in 2026!), 2 Wellness days and 1 Paid Volunteer Day 
• Voucher program for Transportation, Meals & Childcare 
• Remote Working Stipend: €40/month automatically applied in payroll
• Access to tools to support your wellbeing such as the Calm App and an Employee Assistance Program 
• Professional development stipend and learning and development offerings to help you build the skills and connections you need to move forward in your career. 
• Charitable contribution match per team member 

Rithum is an equal opportunity employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates without regard to race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other protected characteristic. All employment is decided on the basis of qualifications, merit, and business need.

We're committed to providing reasonable accommodations in accordance with the law for qualified applicants. If you require assistance during the interview process due to a medical condition or need support accessing our website or completing the application process, please reach out to us by completing the Accommodations Request Form. Your comfort and accessibility are important to us, and we're here to ensure a seamless experience as you explore opportunities with our team.

Rithum™ is the world’s most trusted commerce network, accelerating how brands, suppliers, and retailers work together to deliver seamless e-commerce experiences. We provide an unmatched platform for brands and retailers, enabling them to accelerate growth, optimise operations across channels, scale product offerings and enhance margins.

Today, more than 40,000 companies trust Rithum to grow their business across hundreds of channels, representing over $50 billion in annual GMV. Using our commerce, marketing, and delivery solutions, our customers create optimised consumer shopping journeys from beginning to end.

Overview

As a Senior Data Engineer, you are a key architect in developing, delivering and maintaining intelligent data infrastructure that powers advanced analytics. You are an experienced data engineer with strong ETL pipeline and dimensional modeling skills, who is ready to leverage AI as a powerful collaborator and brings a depth of knowledge to ensure it is employed effectively for the long-term health of our business systems. You are responsible for building complex data pipelines from the ground up, delivering data into and enhancing a database infrastructure that powers advanced analytics, AI-driven decision-making, and autonomous data operations. You work across the organization, supporting and collaborating with our product teams, engineers, data scientists, and data analysts. In this context, you enhance and support our company’s cloud data architecture to support our products and data initiatives, for external clients as well as internal users.

Responsibilities

Core Data Infrastructure 

• Design and implement scalable ETL/ELT workflows that support both batch and streaming data using AWS primitives (e.g., S3, Kinesis, Glue, Redshift, Athena) 
• Architect and maintain cloud-native data platforms with automated ingestion, transformation, and governance pipelines using modern tools like DBT, Apache Spark, Delta Lake, Airflow, and Databricks 
• Work with stakeholders, including the Product, BI, and Support teams, to assist with data-related technical challenges and support their data and infrastructure needs.
• Collaborate with cross-functional Engineering teams using analytics to predict data needs and proactively deliver solutions. 
• Assist in the optimization of data lake/lakehouse infrastructure, to support AI workloads and large-scale analytics. 

Governance & Collaboration 

• Ensure data quality, lineage, and observability.
• Develop and enforce data governance policies, including compliance monitoring and privacy protection. 
• Partner with Data Scientists to optimize data pipelines for model training, inference, and continuous learning workflows. 

Advanced Data Operations 

• Build self-healing data pipelines with AI-driven error detection, root cause analysis, and automated remediation capabilities. 
• Implement intelligent data lineage tracking to automatically discover relationships between datasets and predict downstream impact of changes. 
• Create AI-assisted data discovery systems that help stakeholders find relevant datasets and understand data semantics through natural language interfaces. 
• Participate in on-call rotation, as needed.

AI-Enhanced Development

• Leverage AI coding assistants (GitHub Copilot, Cursor, etc.) to
• Accelerate development cycles, generate complex SQL queries, and automatically optimize data pipeline code. 
• Develop data quality monitoring, using anomaly detection and data profiling tools to identify issues, before they impact downstream systems. 
• Optimize pipeline orchestration, with ML to predict optimal scheduling, resource allocation, and failure recovery patterns.
• Generate and maintain living documentation that evolves with code changes. 

Leadership & Innovation 

• Participate in the full software development lifecycle, including both manual and AI-assisted requirements gathering, automated testing, and intelligent deployment strategies. 
• Mentor junior engineers on both traditional data engineering practices and effective use of AI development tools. 
• Lead tool evaluation and adoption for the data engineering team, establishing best practices for human-AI collaboration. 
• Drive innovation in data architecture by experimenting with emerging technologies.

Qualifications 

Minimum Qualifications  

• 3+ years of experience in data engineering, including building and maintaining large-scale data pipelines
• Extensive experience in SQL RDBMS (SQLServer or similar) with dimensional modeling using star schema, and foundational data warehousing concepts
• Hands-on experience with AWS services such as Redshift, Athena, S3, Kinesis, Lambda, Glue 
• Experience with DBT, Databricks or similar data platform tooling
• Experience working with structured and unstructured data and implementing data quality frameworks
• Excellent communication and collaboration skills 
• Demonstrated experience using AI coding tools (GitHub Copilot, Cursor, or similar), with understanding of prompt engineering, to enhance development productivity 
• Understanding of AI/ML concepts and data requirements, including feature stores, model versioning, and real-time inference pipelines

Preferred Qualifications 

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Experience in a SaaS or e-commerce environment with AI/ML products
• Knowledge of stream processing frameworks like Kafka, Flink, or Spark Structured Streaming 
• Familiarity with LLMOps and AI model deployment patterns in data infrastructure 
• Experience with AI-powered data tools such as automated data catalogs, intelligent monitoring systems, or AI-assisted query optimization
• Proven ability to thrive in a fast-paced, agile environment with shifting priorities and emerging technologies
• Experience with containerization and orchestration tools like Docker and Kubernetes 

Travel Required

Up to 10%

Other Duties

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

What it’s like to work at Rithum 

When you join Rithum, you can expect to work with smart risk-takers, courageous collaborators, and curious minds.

As part of the Rithum team, you are valued, supported, and included. Guided by a transparent culture and accessible, approachable leadership, we offer career opportunities aligned to your ambitions and talents. To ensure work and life balance works for you, we also offer an array of resources to support you and your families, including comprehensive benefits and wellness plans.

At Rithum you will:

• Partner with the leading brands and retailers.
• Connect with passionate professionals who will help support your goals.
• Participate in an inclusive, welcoming work atmosphere.
• Achieve work-life balance through remote-first working conditions, generous time off, and wellness days.
• Receive industry-competitive compensation and total rewards benefits.

Benefits 

• Medical coverage provided through Irish Life Health; premiums paid by the company 
• Life & disability insurance
• Pension plan with 5% company match
• Competitive time off package with 25 Days of PTO, 11 Company-paid holidays, 2 Wellness days and 1 Paid Volunteer Day 
• Access to tools to support your wellbeing such as the Calm App and an Employee Assistance Program 
• €50/month Remote work stipend for internet
• Professional development stipend and learning and development offerings to help you build the skills and connections you need to move forward in your career. 
• Charitable contribution match per team member  

Rithum is an equal opportunity employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates without regard to race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other protected characteristic. All employment is decided on the basis of qualifications, merit, and business need.

We're committed to providing reasonable accommodations in accordance with the law for qualified applicants. If you require assistance during the interview process due to a medical condition or need support accessing our website or completing the application process, please reach out to us by completing the Accommodations Request Form. Your comfort and accessibility are important to us, and we're here to ensure a seamless experience as you explore opportunities with our team.

Position Overview

We are looking to welcome yet another brilliant Senior Marketing Data Analyst into our Marketing Analytics team.

As a Senior Data Analyst, you’ll be responsible for designing and driving high-impact analytics solutions, from developing advanced statistical frameworks to evaluate marketing performance, to building data pipelines that integrate third-party sources, to creating interactive tools that empower partner teams. These are just a few examples of the initiatives you’ll help lead and deliver end-to-end, playing a key role in shaping the technical direction of our analytics efforts. The demands on this team are constantly evolving with the needs of Socialpoint’s and Zynga’s dynamic marketing teams, so it is important that you be able to adapt and utilize your time efficiently.

What you'll do:

• Partner closely with marketing and cross-functional teams to identify growth opportunities, improve efficiency, and shape strategic initiatives.
• Lead analytical deep dives to surface insights and translate them into actionable recommendations for senior stakeholders.
• Visualize and communicate analytical findings clearly, enabling data-driven decision-making across the organization.
• Apply statistical methodologies to evaluate performance and account for uncertainties in major initiatives.
• Proactively explore and prototype opportunities using AI-driven automation to streamline investigations and improve decision-making.

What You Bring: 

• Demonstrated experience with some or all of the following: predictive modeling, statistics, experimental design, optimization, data visualization
• Understanding of marketing metrics and KPIs, with experience in campaign optimization, Lifetime Value (LTV) modeling, and incrementality analysis
• Proficiency in SQL and Python with hands-on experience in Redshift, Databricks, PySpark, and Airflow
• Strong analytical and problem-solving skills with the ability to translate ambiguous questions into data-driven insights
• Strong communication skills — you can explain complex data in simple, actionable terms
• Familiarity with AI/ML concepts or experience in automating recurring analytics workflows is a plus
• A team player, you establish effective relationships to work with others for the win
• Proven work experience in data analytics or data science roles 
• BS in Computer Science, Math, Statistics, Economics, or other quantitative field; Masters, MBA or PhD preferred

What's in it for you as a Socialpointer?

• Hybrid working model: we ask you to come to our Barcelona office at least 2 days per week
• A generous 25 days of annual leave, plus public holidays
• Private medical insurance for you and your family to keep your health bar full
• Disability and life insurance
• Choose from the latest iOS or Android device when you join (phone or tablet)
• Free language lessons in English, Spanish and Catalan
• Spotify Premium to add the perfect soundtrack to your adventure
• Legendary social events and parties to let off some steam
• Take-Two Interactive employee stock purchase plan (eligibility criteria applies)
• Professional development budget for skills training

Onsite perks include:

• State of the art gym facilities
• Free breakfast, lunch, and specialty coffee
• Onsite physiotherapist and hairdresser (no wallet needed!)

The list goes on and on… so get your game on and apply now! Click “Apply” to level up and submit your application in English.

Position Overview

We are looking to welcome yet another brilliant Senior Marketing Data Analyst into our Marketing Analytics team.

As a Senior Data Analyst, you’ll be responsible for designing and driving high-impact analytics solutions, from developing advanced statistical frameworks to evaluate marketing performance, to building data pipelines that integrate third-party sources, to creating interactive tools that empower partner teams. These are just a few examples of the initiatives you’ll help lead and deliver end-to-end, playing a key role in shaping the technical direction of our analytics efforts. The demands on this team are constantly evolving with the needs of Socialpoint’s and Zynga’s dynamic marketing teams, so it is important that you be able to adapt and utilize your time efficiently.

What you'll do:

• Partner closely with marketing and cross-functional teams to identify growth opportunities, improve efficiency, and shape strategic initiatives.
• Lead analytical deep dives to surface insights and translate them into actionable recommendations for senior stakeholders.
• Visualize and communicate analytical findings clearly, enabling data-driven decision-making across the organization.
• Apply statistical methodologies to evaluate performance and account for uncertainties in major initiatives.
• Proactively explore and prototype opportunities using AI-driven automation to streamline investigations and improve decision-making.

What You Bring: 

• Demonstrated experience with some or all of the following: predictive modeling, statistics, experimental design, optimization, data visualization
• Understanding of marketing metrics and KPIs, with experience in campaign optimization, Lifetime Value (LTV) modeling, and incrementality analysis
• Proficiency in SQL and Python with hands-on experience in Redshift, Databricks, PySpark, and Airflow
• Strong analytical and problem-solving skills with the ability to translate ambiguous questions into data-driven insights
• Strong communication skills — you can explain complex data in simple, actionable terms
• Familiarity with AI/ML concepts or experience in automating recurring analytics workflows is a plus
• A team player, you establish effective relationships to work with others for the win
• Proven work experience in data analytics or data science roles 
• BS in Computer Science, Math, Statistics, Economics, or other quantitative field; Masters, MBA or PhD preferred

What's in it for you as a Socialpointer?

• Hybrid working model: we ask you to come to our Barcelona office at least 2 days per week
• A generous 25 days of annual leave, plus public holidays
• Private medical insurance for you and your family to keep your health bar full
• Disability and life insurance
• Choose from the latest iOS or Android device when you join (phone or tablet)
• Free language lessons in English, Spanish and Catalan
• Spotify Premium to add the perfect soundtrack to your adventure
• Legendary social events and parties to let off some steam
• Take-Two Interactive employee stock purchase plan (eligibility criteria applies)
• Professional development budget for skills training

Onsite perks include:

• State of the art gym facilities
• Free breakfast, lunch, and specialty coffee
• Onsite physiotherapist and hairdresser (no wallet needed!)

The list goes on and on… so get your game on and apply now! Click “Apply” to level up and submit your application in English.

• A strong passion for solving complex analytical puzzles
• Proven ability to translate business needs into advanced analytics solutions
• Deep expertise with the modern data stack (BigQuery, Snowflake, dbt, Looker, Airflow, GitHub, command line-based workflows)
• Exceptional SQL skills coupled with at least 5 years of relevant experience in data analytics or engineering roles
• Solid understanding of data modeling principles (e.g., Kimball methodology, star schemas)
• A high valuation of business context and the drive to achieve technical excellence
• An inclination towards collaboration and pride in contributing to high-functioning teams
• Enjoyment in working within fast-paced, growth-oriented environments
• A sense of fun at work, with extracurricular interests like Ping Pong or Mario Kart seen as a bonus!

Scopely is seeking a highly motivated Analytics Engineer to join our Playgami team in Barcelona on a hybrid basis! 

At Scopely, we care deeply about what we do and want to inspire play every day - whether in our work environments alongside our talented colleagues or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing, and innovating the mobile games industry, connecting millions of people worldwide daily.  

Playgami is building the best SaaS gaming platform ever! The team strives to create the world’s best products for game production, operation, and insights. Powering many award-winning, loved-by-millions franchise games over mobile, web, and PC. 

What You’ll Do  

• We collaborate with engineers, product teams, and analysts to create self-serve insight products that are fast, accurate, and elastic at a petabyte-scale
• We work across the full data product lifecycle: designing new tracking plans, developing data models, ELT pipelines, and self-serve insight products like Looker explores and dashboards
• We are stewards of data quality, ensuring that metrics are consistently reported across the catalog of data products
• We work with cutting-edge tech (BigQuery, dbt, Looker)
• We look forward and back, applying tools like BQML to predict player behavior
• We empathize with our game product teams and departments to make their daily work more enjoyable and their products more successful
• We often specialize in some part of the data stack and lifecycle but always aim to contribute across the full spectrum

What We’re Looking For  

• You love solving puzzles
• You can translate needs into analytics tech
• You have experience with the modern data stack (tools like BigQuery, Snowflake, dbt, Looker, Airflow, GitHub, and command line-based workflows) or hunger to work in that domain
• You have first-class SQL skills and 3+ years of experience in a relevant role
• You understand the importance of data modeling, like knowing your Kimballs, your star schemas
• You value business context and improvement as much as you do first-class technical solutions
• You love collaboration and take pride in working in high-functioning teams
• You enjoy working in rapidly evolving, hyper-growth environments where every change presents an opportunity for us to grow
• You love having fun at work. Ping Pong/Mario Kart skills are a plus!

At Scopely, we create games for everyone - and want to ensure that the people behind our games reflect that!   We are committed to creating a diverse, supportive work environment where everyone is treated with respect. We are committed to providing equal employment opportunities and welcome individuals from all backgrounds to join us & embrace the adventure!  

• Lead and collaborate with engineers, product teams, and analysts to develop self-serve insight products that are responsive, precise, and scalable at petabyte levels
• Oversee the entire data product lifecycle, including designing new tracking plans, developing data models, ELT pipelines, and self-serve insight products like Looker explores and dashboards
• Act as a guardian of data quality, ensuring consistent metric reporting across a wide range of data products
• Establish and maintain robust data observability practices—including automated data validation, anomaly detection, SLAs, and alerting—to ensure trust and reliability across the pipeline
• Utilize cutting-edge technology stack including BigQuery, dbt and Looker
• Provide technical leadership and empathize with game product teams and departments to enhance their daily operations and product success
• Bring expertise in a specific part of the data stack and lifecycle while contributing broadly across all aspects
• Mentor team members and drive the adoption of best practices within the team

• A strong passion for solving complex analytical puzzles
• Proven ability to translate business needs into advanced analytics solutions
• Deep expertise with the modern data stack (BigQuery, Snowflake, dbt, Looker, Airflow, GitHub, command line-based workflows)
• Exceptional SQL skills coupled with at least 5 years of relevant experience in data analytics or engineering roles
• Solid understanding of data modeling principles (e.g., Kimball methodology, star schemas)
• Hands-on experience with data observability frameworks and data validation methods (e.g., dbt tests, schema testing, anomaly detection, SLAs/SLIs, lineage tools)
• A high valuation of business context and the drive to achieve technical excellence
• An inclination towards collaboration and pride in contributing to high-functioning teams
• Enjoyment in working within fast-paced, growth-oriented environments
• A sense of fun at work, with extracurricular interests like Ping Pong or Mario Kart seen as a bonus!

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.

Join Us as We Build the Datavant Life Sciences Tech Hub in Barcelona

Datavant is expanding its global footprint with the development of our Life Sciences Tech Hub in Barcelona. We are seeking talented technical professionals who are product-oriented, impact-driven, and motivated to help shape the future of healthcare technology.

At Datavant, our Life Sciences technology powers clinical research, real-world evidence generation, pharmacovigilance, and data collaboration across the healthcare ecosystem. As a Software Engineer in our Life Sciences Tech Hub, you will design and build systems that enable secure, privacy-preserving access to high-quality healthcare data used by pharmaceutical companies, biotech innovators, and research organizations worldwide. Your work will directly support the development of new therapies, accelerate clinical trials, and improve patient outcomes by ensuring that critical data is interoperable, scalable, and trustworthy.

Careers at Datavant offer the chance to apply your technical expertise and problem-solving skills in support of our mission: enabling every healthcare decision to be powered by the right data, at the right time, in the right format. We’re looking for problem-solvers, game-changers, innovators, dreamers, doers - people who are ready to move the needle and build on our success.

Why join Datavant’s tech team? 

• You’ll collaborate with other engineering leaders on all matters that impact the Engineering team, including resourcing and building technology/product vision
• You’ll have the opportunity to coach and mentor colleagues, including code reviews, higher-level software design, and direct management
• The team works on a technical stack which includes both cloud and on-premise deployments, big-data ingestion and analytics, distributed systems, and algorithmic complexity.

Data Engineer (Python, Spark, Snowflake)

The Role

As a Data Engineer, you will build and scale health data pipelines that enable data discoverability, linkage, privacy, machine learning, and analytics across the organization. You will work with Python, Spark, and Snowflake to design efficient data models and reliable processing frameworks. This role provides the opportunity to shape foundational data infrastructure that supports regulatory-grade health decisions at scale.

What You’ll Do

• Design and maintain scalable data pipelines using Python, Spark, and Airflow
• Ensure pipeline reliability, data quality, and observability
• Partner with Science and Product to define and prioritize data requirements
• Implement automated testing and optimize processing performance and cost
• Design and maintain data validation frameworks aligned with regulatory requirements

What You’ll Bring

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience
• 2+ years of data engineering or software engineering experience for junior candidates; 5+ years for senior candidates
• Professional experience building data pipelines in Python
• Hands on experience with distributed data processing frameworks such as Apache Spark and orchestration with Airflow
• Experience working with cloud data warehouses such as Snowflake
• Experience integrating agentic code generation tools such as Claude Code or Codex into day to day software engineering practices

Preferred Qualifications

• Experience designing dimensional or analytics data models
• Experience working in AWS-based data environments
• Experience implementing data governance and quality frameworks
• Understanding of architectural considerations for on premises deployments, including networking and security constraints
• Knowledge of application security best practices (vulnerability management, security posture management, and risk assessment) and compliance frameworks (HIPAA, GDPR, HITRUST)

Perks of joining Datavant in Barcelona

• Competitive and equitable salary
• Hybrid work model, with two days per week based in our Gràcia office
• Daily in-office lunch stipend and access to a fully stocked kitchen
• Comprehensive private health insurance, including out-of-network reimbursement options
• 25 days of annual paid leave
• Six-week “Work from Anywhere” policy 

Are you excited about building modern data infrastructure that powers self-service analytics and high-quality data products at scale? At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable, partnering closely with product, analysts, data scientists, and engineering teams to measure what matters.

You’ll be joining a mature and growing community of 40+ data engineers who are shaping one of the most advanced data ecosystems in the industry.

What you'll be doing:

• Design, build, and evolve scalable ETL/ELT pipelines for high-volume, fast-changing datasets
• Own medium-to-large data initiatives end-to-end, from requirement shaping and technical design to production rollout and ongoing improvement
• Model reliable, analytics-ready data using proven warehouse methodologies such as Kimball, Inmon, or similar approaches
• Develop and maintain curated analytical layers, semantic models, and data marts that enable self-service and trusted decision-making
• Orchestrate robust workflows using tools such as Apache Airflow and improve reliability, observability, and maintainability of data pipelines
• Partner with software engineers, analysts, product managers, and business stakeholders to translate ambiguous requirements into scalable data solutions
• Proactively identify data quality, performance, and modeling issues and drive improvements before they become business problems
• Contribute to architecture and engineering decisions within your domain, balancing speed, quality, and long-term maintainability
• Mentor less senior data engineers through code reviews, design discussions, documentation, and day-to-day guidance
• Raise the engineering bar through testing, automation, CI/CD practices, clear documentation, and thoughtful technical standards

We're looking for:

• Strong SQL and Python skills, with solid hands-on experience building production-grade data pipelines and analytical models
• Deep understanding of dimensional modeling methodologies and modern data warehouse design in platforms such as Snowflake, BigQuery, or similar
• Experience owning projects independently and driving delivery across multiple stakeholders or teams
• Solid experience with orchestration tooling such as Airflow, Dagster, or similar
• Strong understanding of data quality, lineage, observability, and operational excellence in a data engineering environment
• Ability to take ambiguous business problems and turn them into clean, maintainable, well-documented data solutions
• Experience working with cloud platforms, preferably AWS, though Azure or GCP experience is also valuable
• Confidence influencing technical decisions within your team and collaborating effectively with both technical and non-technical stakeholders
• Strong communication skills and a collaborative, problem-solving mindset

Bonus points for:

• Experience with event-driven source systems
• Experience with cloud-native analytical databases like Snowflake, BigQuery, Databricks
• Familiarity with semantic layers, metrics modeling, and enabling data products beyond traditional BI reporting
• Exposure to experimentation-driven or product-led environments
• Experience with data governance, cataloging, and documentation practices such as DataHub
• Experience improving developer productivity through tooling, shared frameworks, or reusable patterns
• Multi-cloud exposure and understanding of platform trade-offs

Are you excited about building modern data infrastructure that powers self-service analytics and high-quality data products at scale? At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable, partnering closely with product, analysts, data scientists, and engineering teams to measure what matters.

You’ll be joining a mature and growing community of 40+ data engineers who are shaping one of the most advanced data ecosystems in the industry.

What you'll be doing:

• Design, build, and evolve scalable ETL/ELT pipelines for high-volume, fast-changing datasets
• Own medium-to-large data initiatives end-to-end, from requirement shaping and technical design to production rollout and ongoing improvement
• Model reliable, analytics-ready data using proven warehouse methodologies such as Kimball, Inmon, or similar approaches
• Develop and maintain curated analytical layers, semantic models, and data marts that enable self-service and trusted decision-making
• Orchestrate robust workflows using tools such as Apache Airflow and improve reliability, observability, and maintainability of data pipelines
• Partner with software engineers, analysts, product managers, and business stakeholders to translate ambiguous requirements into scalable data solutions
• Proactively identify data quality, performance, and modeling issues and drive improvements before they become business problems
• Contribute to architecture and engineering decisions within your domain, balancing speed, quality, and long-term maintainability
• Mentor less senior data engineers through code reviews, design discussions, documentation, and day-to-day guidance
• Raise the engineering bar through testing, automation, CI/CD practices, clear documentation, and thoughtful technical standards

We're looking for:

• Strong SQL and Python skills, with solid hands-on experience building production-grade data pipelines and analytical models
• Deep understanding of dimensional modeling methodologies and modern data warehouse design in platforms such as Snowflake, BigQuery, or similar
• Experience owning projects independently and driving delivery across multiple stakeholders or teams
• Solid experience with orchestration tooling such as Airflow, Dagster, or similar
• Strong understanding of data quality, lineage, observability, and operational excellence in a data engineering environment
• Ability to take ambiguous business problems and turn them into clean, maintainable, well-documented data solutions
• Experience working with cloud platforms, preferably AWS, though Azure or GCP experience is also valuable
• Confidence influencing technical decisions within your team and collaborating effectively with both technical and non-technical stakeholders
• Strong communication skills and a collaborative, problem-solving mindset

Bonus points for:

• Experience with event-driven source systems
• Experience with cloud-native analytical databases like Snowflake, BigQuery, Databricks
• Familiarity with semantic layers, metrics modeling, and enabling data products beyond traditional BI reporting
• Exposure to experimentation-driven or product-led environments
• Experience with data governance, cataloging, and documentation practices such as DataHub
• Experience improving developer productivity through tooling, shared frameworks, or reusable patterns
• Multi-cloud exposure and understanding of platform trade-offs

Are you a Senior Data Engineer with a passion to build, support & maintain digital marketing solutions that offers real value? Are you interested in working with the largest global brands and complex challenges in the media analytics space? Then you might be the Senior Data Engineer we’re looking for!

What will your day look like?

As our new Senior Data Engineer, you will become part of our growing Data Insights and Science team. Here, you will employ new technologies across multiple cloud platforms to help successful brands reach their next level in 1:1 retargeting, communication, and CRM. More specifically, your tasks include:

• Identify, collect, and integrate data from various sources by building high-quality data pipelines and data models for analytics and business intelligence (BI) purposes.
• Develop and optimize code to enable pipelines at minimum cost and ease of maintenance.
• Build monitoring procedures & tools to ensure solid ETL flows and data quality.
• Design processes and tools to correct ETL incidents.
• Collaborate with CRM developers, data scientists, data analysts, and product owners to ensure the supplied data supports the business initiatives.
• Consult our data analytics teams to ensure best practices on the technical use of data are followed.
• Design data architectures and collaborate in data migrations in cloud environments. 

Who are you going to work with?

You will join a team of highly skilled Architects, Data Scientists, and Consultants who are passionate about unlocking insights from data through analytics. You will also get to work closely with experts from other Technology, Creative, and Client Teams.

What do you bring to the table?

As a person, you have a team player mindset and an open-minded attitude. You can communicate ideas and technical topics honestly and clearly – also to non-experts – while respecting the views of others on the team. You are eager to understand and find solutions, allowing you to quickly adapt to changing situations and come up with new ideas.

At the same time, you solve problems in an analytical and pragmatic manner.

Moreover, you have:

• Experience in data engineering, big data, business intelligence, or data science. 
• Experience in Spark, Python, Scala, or similar.
• Excellent SQL skills enabling large-scale data transformation and analysis.
• A comprehensive understanding of cloud data warehousing, data pipelines and data transformation (extract, transform, and load) processes and supporting technologies such as Google Dataflow, Looker, DBT, EMR, CI/CD Pipelines, Airflow DAGs, and other analytics tools.
• Experience with cloud-based data infrastructures (Ideally GCP, but AWS or Azure would also suffice)
• Programming experience in Javascript, Python, or similar.
• Expertise in managing databases, including performance tuning, backup, and recovery.
• Solid knowledge of data quality management best practices, including data profiling, data cleansing, and data validation
• Knowledge of strengths and limitations of visualization tools (e.g. PowerBI, Tableau, Looker, etc.) in terms of data modeling in the visualization tools.
• Understanding of versioning control tools like GitHub to changes related to dbt models and transformations, ensuring that changes are tracked, documented, and reviewed by the appropriate stakeholders.
• Knowledge of applying data governance principles, policies, and practices that ensure data accuracy, consistency, and security
• Knowledge of Kubernetes would be an advantage

Personal skills:

• Strong desire to contribute towards keeping data tidy and well-organized
• Ability to think critically, identify issues autonomously, and propose corrective actions.
• Build great relationships with your team and stakeholders

A leader in personalized customer experiences

VML MAP is a world-leading Centre of Excellence that helps businesses humanize the relationship between the brand and the customer through hyper personalization at scale, marketing automation and CRM. With the brain of a consultancy, the heart of an agency and the power of technology and data, we work with some of the world's most admired brands to help them on their transformation journey to becoming truly customer-centric. Together, we are 1000 + technology specialists, data scientists, strategic thinkers, consultants, operations experts, and creative minds from 55+ nationalities.

A global network

We are part of the global VML network that encompasses more than 30,000 employees across 150+ offices in 60+ markets, each contributing to a culture that values connection, belonging, and the power of differences. 

#LI-EMEA

Are you a Senior Data Engineer with a passion to build, support & maintain digital marketing solutions that offers real value? Are you interested in working with the largest global brands and complex challenges in the media analytics space? Then you might be the Senior Data Engineer we’re looking for!

What will your day look like?

As our new Senior Data Engineer, you will become part of our growing Data Insights and Science team. Here, you will employ new technologies across multiple cloud platforms to help successful brands reach their next level in 1:1 retargeting, communication, and CRM. More specifically, your tasks include:

• Identify, collect, and integrate data from various sources by building high-quality data pipelines and data models for analytics and business intelligence (BI) purposes.
• Develop and optimize code to enable pipelines at minimum cost and ease of maintenance.
• Build monitoring procedures & tools to ensure solid ETL flows and data quality.
• Design processes and tools to correct ETL incidents.
• Collaborate with CRM developers, data scientists, data analysts, and product owners to ensure the supplied data supports the business initiatives.
• Consult our data analytics teams to ensure best practices on the technical use of data are followed.
• Design data architectures and collaborate in data migrations in cloud environments. 

Who are you going to work with?

You will join a team of highly skilled Architects, Data Scientists, and Consultants who are passionate about unlocking insights from data through analytics. You will also get to work closely with experts from other Technology, Creative, and Client Teams.

What do you bring to the table?

As a person, you have a team player mindset and an open-minded attitude. You can communicate ideas and technical topics honestly and clearly – also to non-experts – while respecting the views of others on the team. You are eager to understand and find solutions, allowing you to quickly adapt to changing situations and come up with new ideas.

At the same time, you solve problems in an analytical and pragmatic manner.

Moreover, you have:

• Experience in data engineering, big data, business intelligence, or data science. 
• Experience in Spark, Python, Scala, or similar.
• Excellent SQL skills enabling large-scale data transformation and analysis.
• A comprehensive understanding of cloud data warehousing, data pipelines and data transformation (extract, transform, and load) processes and supporting technologies such as Google Dataflow, Looker, DBT, EMR, CI/CD Pipelines, Airflow DAGs, and other analytics tools.
• Experience with cloud-based data infrastructures (Ideally GCP, but AWS or Azure would also suffice)
• Programming experience in Javascript, Python, or similar.
• Expertise in managing databases, including performance tuning, backup, and recovery.
• Solid knowledge of data quality management best practices, including data profiling, data cleansing, and data validation
• Knowledge of strengths and limitations of visualization tools (e.g. PowerBI, Tableau, Looker, etc.) in terms of data modeling in the visualization tools.
• Understanding of versioning control tools like GitHub to changes related to dbt models and transformations, ensuring that changes are tracked, documented, and reviewed by the appropriate stakeholders.
• Knowledge of applying data governance principles, policies, and practices that ensure data accuracy, consistency, and security
• Knowledge of Kubernetes would be an advantage

Personal skills:

• Strong desire to contribute towards keeping data tidy and well-organized
• Ability to think critically, identify issues autonomously, and propose corrective actions.
• Build great relationships with your team and stakeholders

A leader in personalized customer experiences

VML MAP is a world-leading Centre of Excellence that helps businesses humanize the relationship between the brand and the customer through hyper personalization at scale, marketing automation and CRM. With the brain of a consultancy, the heart of an agency and the power of technology and data, we work with some of the world's most admired brands to help them on their transformation journey to becoming truly customer-centric. Together, we are 1000 + technology specialists, data scientists, strategic thinkers, consultants, operations experts, and creative minds from 55+ nationalities.

A global network

We are part of the global VML network that encompasses more than 30,000 employees across 150+ offices in 60+ markets, each contributing to a culture that values connection, belonging, and the power of differences. 

#LI-EMEA

Are you a Senior Data Engineer with a passion to build, support & maintain digital marketing solutions that offers real value? Are you interested in working with the largest global brands and complex challenges in the media analytics space? Then you might be the Senior Data Engineer we’re looking for!

What will your day look like?

As our new Senior Data Engineer, you will become part of our growing Data Insights and Science team. Here, you will employ new technologies across multiple cloud platforms to help successful brands reach their next level in 1:1 retargeting, communication, and CRM. More specifically, your tasks include:

• Identify, collect, and integrate data from various sources by building high-quality data pipelines and data models for analytics and business intelligence (BI) purposes.
• Develop and optimize code to enable pipelines at minimum cost and ease of maintenance.
• Build monitoring procedures & tools to ensure solid ETL flows and data quality.
• Design processes and tools to correct ETL incidents.
• Collaborate with CRM developers, data scientists, data analysts, and product owners to ensure the supplied data supports the business initiatives.
• Consult our data analytics teams to ensure best practices on the technical use of data are followed.
• Design data architectures and collaborate in data migrations in cloud environments. 

Who are you going to work with?

You will join a team of highly skilled Architects, Data Scientists, and Consultants who are passionate about unlocking insights from data through analytics. You will also get to work closely with experts from other Technology, Creative, and Client Teams.

What do you bring to the table?

As a person, you have a team player mindset and an open-minded attitude. You can communicate ideas and technical topics honestly and clearly – also to non-experts – while respecting the views of others on the team. You are eager to understand and find solutions, allowing you to quickly adapt to changing situations and come up with new ideas.

At the same time, you solve problems in an analytical and pragmatic manner.

Moreover, you have:

• Experience in data engineering, big data, business intelligence, or data science. 
• Experience in Spark, Python, Scala, or similar.
• Excellent SQL skills enabling large-scale data transformation and analysis.
• A comprehensive understanding of cloud data warehousing, data pipelines and data transformation (extract, transform, and load) processes and supporting technologies such as Google Dataflow, Looker, DBT, EMR, CI/CD Pipelines, Airflow DAGs, and other analytics tools.
• Experience with cloud-based data infrastructures (Ideally GCP, but AWS or Azure would also suffice)
• Programming experience in Javascript, Python, or similar.
• Expertise in managing databases, including performance tuning, backup, and recovery.
• Solid knowledge of data quality management best practices, including data profiling, data cleansing, and data validation
• Knowledge of strengths and limitations of visualization tools (e.g. PowerBI, Tableau, Looker, etc.) in terms of data modeling in the visualization tools.
• Understanding of versioning control tools like GitHub to changes related to dbt models and transformations, ensuring that changes are tracked, documented, and reviewed by the appropriate stakeholders.
• Knowledge of applying data governance principles, policies, and practices that ensure data accuracy, consistency, and security
• Knowledge of Kubernetes would be an advantage

Personal skills:

• Strong desire to contribute towards keeping data tidy and well-organized
• Ability to think critically, identify issues autonomously, and propose corrective actions.
• Build great relationships with your team and stakeholders

A leader in personalized customer experiences

VML MAP is a world-leading Centre of Excellence that helps businesses humanize the relationship between the brand and the customer through hyper personalization at scale, marketing automation and CRM. With the brain of a consultancy, the heart of an agency and the power of technology and data, we work with some of the world's most admired brands to help them on their transformation journey to becoming truly customer-centric. Together, we are 1000 + technology specialists, data scientists, strategic thinkers, consultants, operations experts, and creative minds from 55+ nationalities.

A global network

We are part of the global VML network that encompasses more than 30,000 employees across 150+ offices in 60+ markets, each contributing to a culture that values connection, belonging, and the power of differences. 

#LI-EMEA

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?

Senior Data Scientist — Verify V2 Data Products, Insights & Monetization

Mission

Build the quantitative foundation that proves and amplifies Verify v2's value—transforming verification telemetry into a reliable, customer-facing data infrastructure that demonstrates measurable ROI, optimizes channel economics, and lays the groundwork for an autonomous identity and verification platform.

You'll own the end-to-end data pipeline from raw events to customer-visible metrics that answer the question every customer asks: "What is this product actually worth to my business?"

What You'll Own

1. Customer Value Infrastructure (Prove ROI at Every Level)

Build the metrics that quantify customer-specific business impact:

• Design and maintain a real-time Customer ROI Engine calculating cost-per-successful-verification, fraud savings, conversion lift, and time-to-value by customer, segment, and use case
• Create customer-facing Value Dashboards showing verification success rates vs. industry benchmarks, cost efficiency trends, and projected savings
• Develop attribution models connecting verification outcomes to downstream business metrics (account activations, transaction completion, fraud prevented)

Establish pricing intelligence at the customer level:

• Build granular unit economics visibility: cost-to-serve, margin contribution, and channel mix efficiency per customer
• Model willingness-to-pay signals and usage patterns to inform tiered pricing and custom packaging
• Quantify the revenue impact of workflow configurations (Silent Auth-first vs. SMS fallback economics)

2. Channel Performance & Optimization (Make Every Verification Smarter)

Create a single source of truth for channel economics:

• Unified performance metrics across SMS, Voice, Email, WhatsApp, and Silent Authentication: deliverability, latency, conversion rate, cost-per-success, and failure taxonomy
• Country × carrier × channel performance matrices with confidence intervals and anomaly flags
• Real-time channel health monitoring with automated alerting for degradation

Build the intelligence layer for workflow optimization:

• Predictive models for optimal channel routing (next-best-channel given geography, time, customer segment, historical performance)
• Fallback effectiveness analysis: quantify conversion recovery and cost trade-offs for each fallback path
• Silent Authentication signal analysis: success/rejection drivers, speed benchmarks, and UX impact measurement

3. Product Data Platform (Foundation for Autonomy)

Design data architecture that enables autonomous decision-making:

• Define the canonical event schema and taxonomy for all verification touchpoints (API calls, webhook events, workflow steps, outcomes)
• Build certified, versioned datasets powering self-serve analytics, ML models, and customer-facing products
• Implement data quality infrastructure: lineage tracking, anomaly detection, freshness SLAs, and automated reconciliation

Ship ML/analytics products that move toward autonomous verification:

• Conversion propensity models: predict verification success probability in real-time to optimize routing
• Fraud & abuse detection: anomaly scoring for traffic pumping, IRSF patterns, and bot behavior—with automated response recommendations
• Time-to-verify prediction: forecast completion time to enable SLA commitments and dynamic timeout tuning
• Customer segmentation: behavioral and commercial clustering for personalized workflows and pricing

4. Monetization (Turn Data into Revenue)

Develop data products that customers will pay for:

• Verification Intelligence Suite: premium analytics, industry benchmarks, and deliverability diagnostics
• Workflow Optimizer: ML-driven recommendations for channel sequencing, timeout configuration, and fallback strategies by geography and vertical
• Fraud Protection Package: risk scoring, pumping detection, and abuse pattern alerts with quantified savings

Define commercial success:

• Package entitlements, usage thresholds, and upgrade triggers
• Track attach rates, retention lift, and expansion revenue attributable to data products
• Build the business case for each offering with clear ROI narratives

Key Responsibilities

• Own the customer value narrative: Build and maintain the infrastructure that lets every customer (and our sales team) articulate Verify's ROI in dollars and percentages
• Ship production ML systems: From feature engineering through deployment, monitoring, and iteration
• Create reliable, self-serve data products: Dashboards, APIs, and datasets that scale without manual intervention
• Drive pricing and packaging decisions: Provide the quantitative foundation for how we charge and what we bundle
• Partner across the organization: Work with Product, Engineering, Finance, Sales, and Customer Success to embed data into every decision
• Report to leadership: Own KPI narratives on margin drivers, growth levers, and competitive positioning

Success Measures

What "Great" Looks Like

Core Data Science

• Experimentation design and causal inference (A/B testing, CUPED, uplift modeling, instrumental variables)
• Predictive modeling: classification, survival analysis, time series, real-time scoring
• Anomaly detection with adversarial thinking (fraud patterns, traffic manipulation, abuse signals)
• Customer analytics: segmentation, LTV modeling, churn prediction, cohort economics

Data Engineering Fluency

• Strong SQL; Python (pandas, scikit-learn, PySpark); comfortable shipping production code
• Event-driven architecture: streaming pipelines and real-time analysis and adaptation (Apache Flink), webhook processing, idempotency, late-arrival handling
• Data modeling: star schemas, semantic layers, data contracts, metric certification
• MLOps: feature stores, model monitoring, CI/CD for analytics, orchestration (Airflow/Dagster)

Product & Commercial Analytics

• Pricing analytics: unit economics, willingness-to-pay estimation, margin optimization
• Funnel analysis for multi-step, multi-channel workflows
• Dashboard design and narrative clarity (Looker, Tableau, dbt metrics layer)
• Packaging and monetization strategy for data products

Domain Expertise (Highly Valued)

• CPaaS, verification, or 2FA: OTP mechanics, deliverability constraints, carrier relationships
• Silent Authentication: network-based verification, success/rejection drivers, integration patterns
• Fraud and risk: traffic pumping, IRSF, bot detection, abuse economics
• Privacy and compliance: GDPR/CCPA, data minimization, audit requirements, customer-facing data controls

Background

• 5–8+ years in data science/analytics, with ≥2 years building and shipping data products
• Track record of translating ambiguous business questions into measurable outcomes
• Experience in B2B SaaS, identity/auth, fintech, messaging/telecom, or fraud analytics preferred
• Demonstrated ability to influence product and pricing decisions with data

Why This Role Matters

Verification is shifting from a cost center to a strategic differentiator. The data infrastructure you build will:

1. Prove value — Give every customer undeniable evidence of ROI
2. Optimize economics — Make every verification faster, cheaper, and more reliable
3. Enable autonomy — Lay the foundation for a platform that routes, optimizes, and protects without human intervention

You'll shape how Vonage—and our customers—think about identity verification as a measurable, optimizable, intelligent system.

#LI-WW1

Join our Movement and Champion Restaurant Culture! 💚

At TheFork we believe that the best things in life happen around the table, and we are on a mission to connect the world’s favorite restaurants and the broadest community of loyal diners.

Finding the best dining experience for our Diners community or boosting restaurant performance for our Restaurateurs Partners has never been easier thanks to our signature products:

• 📱TheFork App: our free restaurant discovery & booking app that helps you find your next table with ease.
• 💻TheFork Manager: our innovative software tool that digitizes restaurant operations, empowering our Restaurateurs to manage bookings efficiently and boost their revenue.
• 💳TheFork PAY and TheFork Gift Card: quick and easy ways to pay directly from TheFork app

At TheFork, we also believe that people truly make the difference. None of this would be possible without our vibrant Forkies community. Our strong core values—Better Together, Ownership, Respect, and Growth—are the guiding principles of everything we do, shaping our behaviors: “Come as you are,” “Dig in,” and “Make it Memorable”.

TheFork leads the restaurant booking market in Europe and operates in 11 countries. Our offices boast a fully international team working together in a flexible, multicultural, and constructive environment that provides everyone with space to grow, both professionally and personally.

To learn more about TheFork and our Forkies, explore our official site: https://www.careers.thefork.com

What you will do:

We are on a journey to revolutionize our data capabilities through the modernization of our Data Platform, unlocking insights and innovations that will power the company’s future.

We’re looking for a Senior Data Engineering Manager who can lead and inspire teams to drive the future of data in our company. If you’re passionate about leading from the front and pushing boundaries, join us on this journey.

You will lead 2 teams composed of Data Engineers and Data Ops to implement and maintain best practices in data processing, according to the Data Lakehouse approach.

You will work closely with Data Governance, Product Management and Architects to drive platform improvements and support the ever evolving needs of data and engineering teams.

You will:

• Own the data platform roadmaps
• Enhance and maintain robust batch ingestion and validation pipelines.
• Participate in our data transformation program taking direct ownership of the creation of a self-service data platform and contributing to the implementation of data governance principles.
• Collaborate with engineering teams to implement engineering best practices within the data ecosystem.
• Lead by example, fostering a culture of excellence and continuous improvement within the data engineering team, ensuring collaboration and alignment with broader business and product objectives
• Mentor and upskill team members
• Contribute to system architecture designs with Architects.
• Coordinate and run Proofs of Concept (POCs).

You will directly report to the Head of the tribe.

You Must Meet These Critical Qualifications

• Proven leadership and mentorship experience guiding data engineering teams.
• Extensive experience with Data Lakehouse architectures and implementation.
• Solid understanding of Data Mesh, including domain ownership, federated governance, and data product design.
• Solid understanding of Data Governance and Quality, covering metadata management, data lineage, and data observability in general.
• Proven experience using AWS services and familiar with infrastructure as code (Terraform).
• Proficiency in Python, SQL, Snowflake and Airflow.
• Experience with data modeling and knowledge of medallion architecture.

You Can Impress With These Additions

• Experience with Apache Iceberg and Delta Lake.
• Realtime data processing at scale.

What we offer you:

😄 An awesome team

🏠 A permanent contract (that can be useful in life)

⚖️ Flexible working environment (2 days home office per week +  up to 4 total weeks additional flexibility during the summer period and in December to work fully remotely)

💸 Competitive fixed salary  & bonus

🍕 Lunch vouchers available for each working day 

🌎 International teams and a multicultural environment spanning 10 offices across Europe

🤝Highly inclusive working environment

🤸‍♀️ Lifestyle benefits that can be used to reimburse  expenses related to physical and leisure activities, family support, travel etc

🎓 Continuous learning and development programs

😌 Free access to the Calm app to help you build resilience wherever you are in your mental health journey

🐣Dedicated parental leave and caregiver leave policies (12 weeks fully paid)

🏥  Health insurance

👩‍🦽 Life & Disability Insurance at no cost to the employee

🍴 Amazing offices with dining, a coffee point on each floor, and leisure area

🎤 Team building events

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

About the role

As a Data Engineer, you’ll be part of the team responsible for designing and delivering the data products that power Fever’s partner ecosystem — from real-time APIs and dashboards to data exports or automated reports. Our teams leverage modern data platforms (Snowflake, DBT, Airflow, Superset, DataHub, etc.) while developing our own technology to deliver high-quality, reliable, and scalable data products across multiple business domains.

You’ll work at the crossroads of engineering, product, and business, translating complex requirements into elegant and maintainable solutions that create real impact for our clients and internal teams.

What You’ll Do

• Deeply understand Fever’s backend systems and data models, identifying the logic and transformations that connect business processes to data representations.
• Collaborate fluidly with Product Managers, Project Managers, and business stakeholders to translate ideas and reporting needs into clear technical requirements and data structures.
• Develop and optimize ETL/ELT workflows using Python, DBT,  Airflow, and Snowflake, ensuring scalability, maintainability, and reliability.
• Design, build, and maintain partner-facing data products, including APIs (real-time and batch), dashboards, webhooks, and file-based exports.
• Ensure that all data delivered to partners is accurate, consistent, and aligned with the underlying business context.
• Contribute to the architecture, testing, and observability of our data ecosystem, promoting best practices and automation wherever possible.
• Take ownership from idea to delivery — you’ll scope, design, implement, and ship solutions in close collaboration with cross-functional teams.
• Support the evolution of Fever’s data mesh, helping domain teams design data products that follow common engineering and governance standards.

What You Bring

• Fluent in Spanish and English; you’ll communicate in Spanish with local teams and in English with global teams
• A Bachelor’s or Master’s degree in Computer Engineering, Data Engineering, or a related field.
• Strong proficiency in Python, SQL, Airflow, and Snowflake (or similar technologies).
• A deep understanding of data modeling and how complex backend systems generate and expose data across products and domains.
• Proven experience building data products for external consumption, such as APIs, dashboards, and partner-facing data feeds.
• Excellent communication and collaboration skills — you can work seamlessly with business stakeholders and product managers, translating abstract needs into clear data solutions.
• You communicate clearly, think in terms of impact, and make technical decisions grounded in business context.
• You thrive in fast-paced environments, adapt quickly to change, and maintain a strong sense of ownership from concept to delivery.
• Familiarity with modern data practices: version control (Git), CI/CD, testing, and observability.

Nice to Have

• Experience with real-time data platforms as Tinybird or Clickhouse
• Exposure to domains like B2B, Marketing, or Partner Reporting.
• Experience with streaming or near-real-time data (Kafka, Kinesis, etc.).

Why Join Us

This is a unique opportunity to join Fever’s Data team at a key moment of growth. You’ll help design and scale the reporting and data delivery layer that connects our platform with thousands of partners worldwide. You’ll work with a modern data stack, collaborate with talented engineers and product teams, and shape how Fever delivers value through data.

You’ll join a team that values clarity, autonomy, and impact — where engineering excellence and business understanding go hand in hand.

Benefits & Perks

• Flexible schedule
• Opportunity to have a real impact in a high-growth global category leader
• 40% discount on all Fever events and experiences
• Responsibility from day one and professional and personal growth
• Great work environment, international team of talented people to work with!
• Health insurance from Day 1.
• English or Spanish Lessons
• Gympass Membership
• Cobee (tax free allowance on restaurants and transport).
• Possibility to receive in advance part of your salary by Payflow.

Interview process

The interview process will be conducted in Spanish; however, some interviews will require English.

• Talent Interview
• Technical Interview I
• Manager Interview

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive.

By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI.

As part of our team, you will:

• Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.
• Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.
• Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.
• Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.
• Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.
• Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.

We’ll be happy to have you on our team if you have:

• Hands-on experience with modern MLOps tooling, including Kubernetes, Cloud providers (GCP and AWS), and ML orchestration frameworks.
• A solid understanding of the ML lifecycle from idea to the customer-facing application.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions.
• Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity.
• At least three years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as ZenML, Dagster, and Airflow.
• Developing infrastructure components and services using cluster solutions like Kubernetes.
• The development of Python-based backend services.
• Creating and maintaining ML pipelines, including legacy ones.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.

We’d be especially thrilled if you have experience with: 

• LLM inference frameworks such as vLLM, DeepSpeed, and TensorRT.
• Writing and maintaining Python libraries used by internal (or external) ML engineers.
• A strong theoretical background in NLP and transformer-based approaches.
• Writing code in Java and/or Kotlin.

#LI-HYBRID
#LI-MR1

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs.

We’re building multi-step coding agents that can understand large codebases, plan changes, call tools, and iterate with the user. As a Research Engineer in the Agentic Models team, you’ll be responsible for the models, training loops, and evaluation pipelines that power these agents.

You’ll work at the intersection of SFT and RL-style post-training, and product-driven evaluation, using our distributed GPU and MapReduce clusters to ship models into JetBrains products.

As part of our team, you will:

• Design, implement, and maintain SFT and RL post-training pipelines for multi-step coding agents.
• Train and adapt LLMs for agent workflows, including planning, tool use, and multi-step interactions inside JetBrains IDEs.
• Build and develop evaluation and simulation environments where coding agents can act, be measured, and compared on realistic developer tasks.
• Design evaluation frameworks and metrics for agent behavior, analyze traces and logs, and close the loop from evaluation back into training, data, and reward design.
• Analyze training and evaluation results to propose and implement improvements to model architectures, training recipes, and datasets.
• Work with large-scale infrastructure, including distributed training on GPU clusters and large MapReduce-style data processing for pre-training and fine-tuning datasets.
• Collaborate closely with research, product, and infrastructure teams to turn high-level product visions into concrete models, experiments, and shipped features. 

We’ll be happy to bring you on board if you have:

• Extensive hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting.
• Deep expertise in modern deep learning frameworks such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar).
• Strong theoretical and practical understanding of LLM fundamentals: architectures, tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A product-aware mindset – you care about how developers actually use agents and can translate product needs and failure modes into modeling and evaluation work.
• At least 3 years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, and/or job schedulers like Kubernetes or SLURM.
• Large-scale data and training pipelines, e.g. MapReduce-style clusters, multi-node GPU training, or workloads on the order of 1M+ CPU/GPU hours.
• Designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks.
• AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.
• Inference optimization and serving optimized models in production.

#LI-KP1

We are one of the largest sports betting operators across Europe and have recently started our expansion into Brazil, making 1000+ location networks work across multiple geographies. If you ever wanted to see how software can handle 90 million bets per month - why not join us?

We have offices based in Madrid but will be offering full flexibility with occasional meet-ups with your teams and leads in the office as well as collaboration with our offices in London, Zagreb and more!

We are looking for someone who has:

• A minimum of 4+ years of hands-on experience in a large scale production environment.
• Has experience engineering high-quality, highly scalable software in any object-oriented or Functional language
• A willingness to learn new technologies
• A talent for clean coding, simple solutions, automated testing, and continuous deployment
• A passion for working in the cloud and automation
• Experience working with distributed systems
• Experience building and improving upon observability
• A passion for creating user-centric, data driven solutions

Bonus points for:

• Experience in AWS (DynamoDB, OpenSearch, MSK, S3, Cognito etc..)
• An interest in Functional Programming
• Knowledge of Kubernetes, Terraform
• Prior experience with data engineering principles—specifically involving Airflow, Kafka, or Snowflake—is a plus

What you'll be doing:

• Collaborating closely with geographically distributed engineering teams to design and implement scalable and robust software solutions.
• Enhancing the existing platform to increase the amount of business functionality driven by end-user configuration
• Enhancing system automation (scale, resiliency, deployment)
• Maintaining, enhancing and creating common platform components and libs (AWS, Erlang, Go, Kafka)
• Working with technical and non-technical stakeholders from the wider organization to understand and drive requirements and improvements across the platform
• Building on our CloudNative platform, enabling more use of AWS technology to aid in speeding up delivery, scale, and resiliency
• Building on our observability tooling and infrastructure to better understand the capabilities of our systems
• Growing the engineering community, building on the existing process and practices
• Leading initiatives and tasks and driving them to completion
• Drive continuous improvement initiatives to enhance team productivity and efficiency.

Are you excited about building analytics foundations that people can truly rely on, turning complex business questions into trusted datasets, metrics, and reporting experiences? At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable, partnering with product, commercial, and engineering teams to measure what matters.

You’ll be joining a mature and growing community of 40+ data engineers and analytics engineers who are shaping one of the most advanced data ecosystems in the industry.

What you'll be doing:

• Design and build curated analytical datasets, metric implementation, and semantic models that enable consistent self-service analytics across the company
• Work hands-on with data warehouse modelling to turn evolving product and business needs into scalable, reusable data structures
• Partner closely with product, data scientists and business stakeholders to clarify requirements and translate them into reliable data models and reporting-ready outputs
• Build and own production dashboards (Tableau) on top of curated datasets and metric definitions, ensuring correctness, performance, and a consistent “single source of truth”
• Contribute to data quality, observability, lineage, and documentation practices to increase trust and reduce firefighting
• Promote reuse over reinvention, identify ad-hoc logic in reporting views or custom SQL and refactor it into curated, high-quality models that multiple teams can rely on.
• Raise the engineering bar through reviews, testing, automation, and pragmatic architectural improvements
• Apply engineering rigor to analytics - treat semantics as code utilizing version control, testing, automation, and CI/CD practices to manage the lifecycle of our business logic.
• Drive self-service adoption - create the foundations that allow analysts and business users to explore data safely and independently, without needing to reinvent the wheel.
• Work embedded within Data Engineering squads, collaborating daily with both data engineers and analysts on shared foundations and end-to-end delivery

We're looking for:

• Strong SQL skills and proven experience building analytical datasets and metrics in a modern data warehouse (Snowflake preferred, BigQuery, Redshift and similar also valuable)
• Solid understanding of data warehouse modeling and best practices (dimensional modeling, fact/dimension design, grains, slowly changing dimensions, semantic consistency)
• Experience working with reporting and BI tools (Tableau preferred), including understanding how data sources, extracts, and dashboard logic impact correctness, performance, and trust
• A production mindset: you care about reliability, maintainability, documentation, and operational ownership, not just creating a dataset once
• Strong ownership and collaboration skills, able to drive clarity in ambiguous problem spaces and partner effectively with both technical and non-technical teams
• Excellent communication skills with a pragmatic, problem-solving approach

Bonus points for:

• Experience with orchestration and workflow tooling (Airflow or similar)
• Experience with data cataloging, lineage, and governance tooling (e.g., DataHub)
• Background in product-led, experimentation-driven, or high-growth environments where definitions evolve quickly
• Experience supporting downstream operational consumers (e.g., CRM/audience platforms) or ML/feature engineering use cases
• Familiarity with streaming/event-heavy ecosystems (Kafka or similar)

Are you excited about building analytics foundations that people can truly rely on, turning complex business questions into trusted datasets, metrics, and reporting experiences? At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable, partnering with product, commercial, and engineering teams to measure what matters.

You’ll be joining a mature and growing community of 40+ data engineers and analytics engineers who are shaping one of the most advanced data ecosystems in the industry.

What you'll be doing:

• Design and build curated analytical datasets, metric implementation, and semantic models that enable consistent self-service analytics across the company
• Work hands-on with data warehouse modelling to turn evolving product and business needs into scalable, reusable data structures
• Partner closely with product, data scientists and business stakeholders to clarify requirements and translate them into reliable data models and reporting-ready outputs
• Build and own production dashboards (Tableau) on top of curated datasets and metric definitions, ensuring correctness, performance, and a consistent “single source of truth”
• Contribute to data quality, observability, lineage, and documentation practices to increase trust and reduce firefighting
• Promote reuse over reinvention, identify ad-hoc logic in reporting views or custom SQL and refactor it into curated, high-quality models that multiple teams can rely on.
• Raise the engineering bar through reviews, testing, automation, and pragmatic architectural improvements
• Apply engineering rigor to analytics - treat semantics as code utilizing version control, testing, automation, and CI/CD practices to manage the lifecycle of our business logic.
• Drive self-service adoption - create the foundations that allow analysts and business users to explore data safely and independently, without needing to reinvent the wheel.
• Work embedded within Data Engineering squads, collaborating daily with both data engineers and analysts on shared foundations and end-to-end delivery

We're looking for:

• Strong SQL skills and proven experience building analytical datasets and metrics in a modern data warehouse (Snowflake preferred, BigQuery, Redshift and similar also valuable)
• Solid understanding of data warehouse modeling and best practices (dimensional modeling, fact/dimension design, grains, slowly changing dimensions, semantic consistency)
• Experience working with reporting and BI tools (Tableau preferred), including understanding how data sources, extracts, and dashboard logic impact correctness, performance, and trust
• A production mindset: you care about reliability, maintainability, documentation, and operational ownership, not just creating a dataset once
• Strong ownership and collaboration skills, able to drive clarity in ambiguous problem spaces and partner effectively with both technical and non-technical teams
• Excellent communication skills with a pragmatic, problem-solving approach

Bonus points for:

• Experience with orchestration and workflow tooling (Airflow or similar)
• Experience with data cataloging, lineage, and governance tooling (e.g., DataHub)
• Background in product-led, experimentation-driven, or high-growth environments where definitions evolve quickly
• Experience supporting downstream operational consumers (e.g., CRM/audience platforms) or ML/feature engineering use cases
• Familiarity with streaming/event-heavy ecosystems (Kafka or similar)

We are looking for a highly motivated Software Engineer in our Furnishing Platform team to build scalable systems and data pipelines to power our consumer credit reporting. You will partner closely with our Product, Compliance, Servicing, and Credit teams to design robust reporting systems. The systems you will work on are vital for delivering accurate and timely data from Affirm’s financial product portfolio to Consumer Reporting Agencies.

Affirm is growing fast and we want you to enable us to scale our products to 10x and beyond through building world-class systems which enable Affirm in its mission to provide honest financial products which improve lives.

We are only just getting started! Come join us as we build a beloved, lasting financial services brand predicated on honesty and trust. It’s going to be an amazing ride!

What You’ll Do

• Own and deliver strategic outcomes: Drive the definition and delivery of quarterly and long-term goals, ensuring your team’s work ladders up to company-wide objectives. Lead engineers through ambiguity and open-ended problems, providing clarity and direction.
• Shape architecture and technical strategy: Influence the design of large-scale data and backend systems across multiple teams. Ensure that solutions are scalable, extensible, and aligned with broader engineering standards.
• Collaborate cross-functionally: Partner with product, analytics, and design to define data-driven solutions. Anticipate risks, articulate trade-offs, and ensure technical decisions support long-term product and business needs.
• Champion operational excellence: Ensure high availability and reliability of data pipelines and services by establishing strong monitoring, alerting, and recovery practices. Drive improvements that reduce system fragility and operational burden.
• Mentor and grow talent: Guide engineers within and beyond your team through mentorship, code/design reviews, and technical leadership. Set high standards for engineering practices and foster a culture of ownership and continuous learning.
• Scale impact beyond your team: Author technical proposals, share best practices via documentation and tech talks, and advocate for improvements that raise the bar for the broader data engineering community.
  
  What We Look For

• Deep technical expertise: 4+ years of experience designing and building large-scale data pipelines and distributed backend systems, with strong proficiency in languages like Python, Kotlin, or similar.
• Systems at scale: Proven track record of delivering high-volume, highly available systems using technologies like AWS, MySQL, Airflow, Spark, and Kubernetes.
• Architectural leadership: Experience defining technical strategies for complex, cross-team initiatives. Ability to design elegant, extensible systems that balance short-term needs with long-term scalability.
• Operational rigor: Skilled at building resilient systems with monitoring, alerting, and safe deployment practices. Comfortable driving significant changes in large, complex codebases.
• Leadership and influence: History of mentoring engineers, unblocking teams, and shaping best practices beyond your immediate group. Ability to navigate ambiguity and drive clarity across stakeholders.
• Strong communication: Excellent verbal and written skills that enable you to influence technical and product decisions across a global engineering org.

Compensation & Benefits

Base Pay Grade - N   

Equity Grade - Poland 4     

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. 

Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).

POL base pay range per year: 301,000 - 401,000 zł    

Additional benefits include:

• Type of employment: Contract of Employment
• Flexible Spending Wallets for tech, food and lifestyle
• Away Days - wellness days to take off work and recharge
• Learning & Development programs
• Parental benefits
• Employee Resource & Community Groups
• This role is eligible for creative tax benefits, subject to applicable law and company policy

The majority of our roles can be located anywhere in Poland.

**This job description is not a contractual document, and is not intended to have binding force.**

#LI-Remote

We are looking for a highly motivated Software Engineer in our Furnishing Platform team to build scalable systems and data pipelines to power our consumer credit reporting. You will partner closely with our Product, Compliance, Servicing, and Credit teams to design robust reporting systems. The systems you will work on are vital for delivering accurate and timely data from Affirm’s financial product portfolio to Consumer Reporting Agencies.

Affirm is growing fast and we want you to enable us to scale our products to 10x and beyond through building world-class systems which enable Affirm in its mission to provide honest financial products which improve lives.

We are only just getting started! Come join us as we build a beloved, lasting financial services brand predicated on honesty and trust. It’s going to be an amazing ride!

What You’ll Do

• Own and deliver strategic outcomes: Drive the definition and delivery of quarterly and long-term goals, ensuring your team’s work ladders up to company-wide objectives. Lead engineers through ambiguity and open-ended problems, providing clarity and direction.
• Shape architecture and technical strategy: Influence the design of backend systems across  multiple teams. Ensure that solutions are scalable, extensible, and aligned with broader engineering standards.
• Collaborate cross-functionally: Partner with product, analytics, and design to define solutions. Anticipate risks, articulate trade-offs, and ensure technical decisions support long-term product and business needs.
• Champion operational excellence: Ensure high availability and reliability of  services by establishing strong monitoring, alerting, and recovery practices. Drive improvements that reduce system fragility and operational burden.
• Mentor and grow talent: Guide engineers within and beyond your team through mentorship, code/design reviews, and technical leadership. Set high standards for engineering practices and foster a culture of ownership and continuous learning.
• Scale impact beyond your team: Author technical proposals, share best practices via documentation and tech talks, and advocate for improvements that raise the bar for the broader data engineering community.
• On-Call Rotation - There would be an on-call rotation for this role as a requirement

What We Look For

• Deep technical expertise: 4+ years of experience designing and building large-scale distributed backend systems, with strong proficiency in languages like Kotlin (or Python as a plus)
• Systems at scale: Proven track record of delivering high-volume, highly available systems using technologies like AWS, MySQL, and Kubernetes (Airflow, Spark, as a plus).
• Architectural leadership: Experience defining technical strategies for complex, cross-team initiatives. Ability to design elegant, extensible systems that balance short-term needs with long-term scalability.
• Operational rigor: Skilled at building resilient systems with monitoring, alerting, and safe deployment practices. Comfortable driving significant changes in large, complex codebases.
• Leadership and influence: History of mentoring engineers, unblocking teams, and shaping best practices beyond your immediate group. Ability to navigate ambiguity and drive clarity across stakeholders.
• Strong communication: Excellent verbal and written skills that enable you to influence technical and product decisions across a global engineering org. Must be proficient in asynchronous mode of communication–written tech specs, wiki, project plans, etc.
• Project management: high degree of organization and ability to surface critical information effectively.

Compensation & Benefits

Base Pay Grade - N

Equity Grade - Spain 4

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. 

Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).

ESP base pay range per year: €85,000 - €115,000

Additional benefits include:

• Flexible Spending Wallets for tech, food and lifestyle
• Away Days - wellness days to take off work and recharge
• Learning & Development programs
• Parental benefits
• Employee Resource & Community Groups

Location - Remote Spain

We are able to offer visa sponsorship for this role, but do require that someone is based in Spain for the role.

Are you excited about building modern data infrastructure that empowers self-service analytics at scale? At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable—partnering with product and business teams to measure what matters.
You’ll be joining a mature and growing community of 40+ data engineers who are shaping one of the most advanced data ecosystems in the industry.

What you'll be doing:

• design, build, and optimize scalable ETL/ELT pipelines for high-volume, fast-changing datasets
• apply proven data warehouse methodologies (e.g. Kimball, Inmon) to design and deliver trustworthy, performant data models
• develop and maintain semantic layers and curated data marts to enable analytical self-service across the company
• orchestrate reliable workflows with modern tooling such as Apache Airflow
• enforce data quality, lineage, and observability practices to ensure confidence in our data products
• partner with product, analytics, and engineering teams to co-create scalable data solutions that deliver measurable business value
• raise the engineering bar through code reviews, testing, automation, and architectural improvements

We're looking for:

• strong SQL and Python skills, with solid understanding of distributed data systems and modern data architectures
• deep knowledge of dimensional data modeling (Kimball, Inmon) and hands-on experience building analytical layers in DWHs such as Snowflake or BigQuery
• hands-on experience with cloud platforms (AWS preferred, Azure/GCP also valuable)
• workflow orchestration experience with Airflow or similar tools
• strong ownership mindset—able to work independently, structure work, and partner effectively with technical and non-technical stakeholders
• excellent communication skills with a collaborative, problem-solving approach
• based in Zagreb as this will require hybrid work

Bonus points for:

• experience with real-time streaming technologies (Kafka or similar)
• experience with cloud native Analytical databases like Snowflake
• multi-cloud exposure and understanding of platform trade-offs
• background in product-led or experimentation-driven environments
• experience with data governance, cataloging, and documentation practices (e.g. DataHub)

About Superbet & Core Experience

Superbet is building the future of entertainment across Europe and Brazil. With millions of monthly active users and over €1B in annual revenue, our Core Experience area owns the surfaces that shape how players discover, play, and engage every day.

Within Core Experience, the Explore tribe drives the experiences that help players find what they love — from our homepage and navigation to our search and discovery systems.

We’re now looking for a Senior or Staff Backend Engineer to help us build the next-generation Search platform that powers discovery across all of Superbet.

The mission

Today, our search experience is fragmented - each vertical (Sports, Casino, Superscore, Supersocial) maintains its own implementation, leading to inconsistent behavior, higher maintenance costs, and missed opportunities for discovery and conversion.

Your mission will be to design, build, and scale a unified search platform that connects these experiences into a single, high-performing system capable of serving millions of queries per day.

You’ll work at the intersection of backend systems, data pipelines, and relevance engineering — shaping how users find and explore content across products, platforms, and geographies.

What you’ll do

• Design and implement distributed backend services that power real-time search and discovery across multiple product verticals.
• Build and optimize indexing, retrieval, and ranking pipelines (e.g., combining BM25 keyword retrieval with vector embeddings and personalization signals).
• Partner with ML, Infra, and Product teams to evolve search relevance, ranking, and experimentation frameworks.
• Architect and evolve API contracts to support multiple clients (web, mobile, internal tools) with low-latency, high-availability performance.
• Drive the technical direction for Search - influencing architecture, observability, scalability, and cost efficiency.
• Contribute to a shared Search platform that other verticals (Sports, Casino, etc.) can extend and build upon.
• Mentor engineers across the Explore tribe, raising the bar for backend design and operational excellence.

Why this role matters

• Search is one of Superbet’s most strategic growth levers - driving discovery, engagement, and conversion across all experiences.
• You’ll shape the core architecture and evolution of a multi-tenant search platform serving millions of players.
• You’ll have significant technical ownership and leadership visibility, collaborating directly with senior engineers, data scientists, and product leaders.
• You’ll be part of a team building the foundations for personalized, context-aware, and experimentation-driven search.

We are looking for

• 6+ years of backend engineering experience (preferably in distributed systems, data platforms, or search domains).
• Deep knowledge of one or more backend languages (Python, Kotlin, Java, Go, Elixir) and proficiency in API design and microservice architecture.
• Experience with search technologies (OpenSearch, Elasticsearch, Lucene, or vector databases such as Pinecone or FAISS).
• Familiarity with indexing pipelines, ranking models, embeddings, or relevance tuning.
• Hands-on experience with streaming and data processing frameworks (Kafka, Spark, Flink, Airflow, etc.).
• Solid understanding of scalability, caching, and performance optimization in high-traffic systems.
• Experience integrating backend services into CI/CD pipelines and monitoring via Datadog, Grafana, or similar tools.
• Strong communication, collaboration, and the ability to work effectively in cross-functional teams.
• Bachelor’s or Master’s degree in Computer Science or a related field.

Bonus points

• Experience designing or operating multi-tenant or cross-domain platforms.
• Background in search relevance, feature stores, or personalization pipelines.
• Exposure to experimentation and A/B testing frameworks.
• Comfort with infrastructure-as-code (Terraform, AWS CDK) and container orchestration (Kubernetes).

Are you excited about building modern data infrastructure that empowers self-service analytics at scale? At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable—partnering with product and business teams to measure what matters.
You’ll be joining a mature and growing community of 40+ data engineers who are shaping one of the most advanced data ecosystems in the industry.

What you'll be doing:

• design, build, and optimize scalable ETL/ELT pipelines for high-volume, fast-changing datasets
• apply proven data warehouse methodologies (e.g. Kimball, Inmon) to design and deliver trustworthy, performant data models
• develop and maintain semantic layers and curated data marts to enable analytical self-service across the company
• orchestrate reliable workflows with modern tooling such as Apache Airflow
• enforce data quality, lineage, and observability practices to ensure confidence in our data products
• partner with product, analytics, and engineering teams to co-create scalable data solutions that deliver measurable business value
• raise the engineering bar through code reviews, testing, automation, and architectural improvements

We're looking for:

• strong SQL and Python skills, with solid understanding of distributed data systems and modern data architectures
• deep knowledge of dimensional data modeling (Kimball, Inmon) and hands-on experience building analytical layers in DWHs such as Snowflake or BigQuery
• hands-on experience with cloud platforms (AWS preferred, Azure/GCP also valuable)
• workflow orchestration experience with Airflow or similar tools
• strong ownership mindset—able to work independently, structure work, and partner effectively with technical and non-technical stakeholders
• excellent communication skills with a collaborative, problem-solving approach
• based in Madrid or surrounding area as this will require hybrid work

Bonus points for:

• experience with real-time streaming technologies (Kafka or similar)
• experience with cloud native Analytical databases like Snowflake
• multi-cloud exposure and understanding of platform trade-offs
• background in product-led or experimentation-driven environments
• experience with data governance, cataloging, and documentation practices (e.g. DataHub)