This is a high-bar IC role on a team building Data APIs, custom visualisations, and AI products that sit at the core of how hoteliers understand and act on their revenue data. You'll work across the full stack — from problem discovery with Product through to production monitoring — and you'll bring the engineering judgment to navigate legacy code, build new systems when needed, and raise the bar for the engineers around you. We care more about how you think than which languages you've used, though Java proficiency is required.

What Makes Us Different?

Duetto is the hospitality industry's leading revenue management platform, founded in 2012 by former Wynn Resorts executives who knew the industry needed better technology. We built the world's first Revenue & Profit Operating System — a suite of tools (GameChanger, ScoreBoard, BlockBuster, Advance and more) that goes beyond room pricing to give hotels, resorts and casinos a complete picture of their revenue and profitability. Trusted by clients ranging from independent boutique hotels to global chains, we've been named the #1 Revenue Management Software by HotelTechAwards four years running and the #1 Best Place to Work in Hotel Tech in 2025. Backed by GrowthCurve Capital since 2024, we're accelerating our investment in AI — and we're genuinely passionate about the industry we serve. We build products we're proud of, for customers we care about.

What You'll Be Doing

• You'll build and ship full-stack features end-to-end — from understanding the problem with Product, breaking down PRDs into well-scoped work, thinking through edge cases before code is written, all the way through to production monitoring and support.
• You'll experiment with AI-assisted workflows across the development lifecycle — from PRD to tickets to implementation — and push what's possible with AI development tooling in a team that takes this seriously.
• You'll navigate and improve legacy code with care and judgment — understanding what's there, why it exists, and how to move it forward safely without creating downstream risk.
• You'll build new systems from scratch when the problem calls for it, bringing strong systems thinking to every decision about how components fit together, how data flows, and where trade-offs matter.
• You'll develop deep fluency in Duetto's data and the hospitality domain — using that understanding to make better product and technical decisions, not just implement requirements.
• You'll mentor engineers through pairing, code review, and the kind of day-to-day craft conversations that raise the bar for how the whole team works.

What We're Looking For

You may be a good fit if you have:

• Demonstrated seniority in full-stack software engineering with production experience across both backend and frontend layers
• Experience as technical lead on multiple projects that shipped to production
• Experience mentoring engineers and raising team-wide engineering quality
• Hands-on experience with AI development tools and a genuine drive to push what's possible with them
• Strong proficiency in Java
• Frontend capability — not expected to be a specialist, but able to ship frontend work independently
• Experience building and maintaining Data APIs
• Proficiency with SQL and NoSQL databases
• Strong systems thinking — you understand how components fit together, how data flows, and where trade-offs matter
• A background in B2C products with strong UX sensibility, or substantial enterprise software experience

Strong candidates may also have:

• Experience with React, TypeScript, and GraphQL
• Familiarity with AWS
• Experience with data modelling and complex, domain-specific data models
• Enterprise and SaaS software background
• Hospitality technology industry experience

Why Duetto?

• AI-first engineering, for real. This team is actively experimenting with AI-assisted workflows across the entire development lifecycle — you won't just be using Copilot to autocomplete, you'll be pushing what AI-augmented development actually means in practice.
• Work that requires genuine domain depth. The Detect & Explore team builds products that help hoteliers understand and act on complex revenue data — the problems are interesting, the data is rich, and the domain rewards curiosity.
• Staff-level ownership. This is a high-autonomy IC role with real technical influence — you'll shape how the team works, mentor engineers, and make architectural decisions that matter.
• Full-stack scope with a high UX bar. Whether your background is B2C or enterprise, you'll be building products where the quality of the end-user experience is taken seriously — not an afterthought.
• A team that cares about craft. Low ego, high standards, and genuine investment in how engineers grow — the kind of environment where Staff engineers thrive.

The Details

• Location: Remote (Croatia)
• Reporting Line: Director of Engineering

Duetto is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law.

Sound like you?

You don't need to have worked in hospitality or checked every box above. If you're a strong full-stack engineer with genuine technical leadership experience, a curiosity for hard data problems, and a drive to work at the frontier of AI-augmented development — we'd love to hear from you.

#LI-REMOTE

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

Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.

The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.

Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives
We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. 

Unicorn momentum
In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

About the role

Databases are notoriously hard to optimize—with 350+ configuration parameters in PostgreSQL alone, even experienced engineers struggle to find the right settings. Have you ever dreamed about a database that continuously self-optimizes itself in the background, so you can focus on what really matters: building great products?

Sometimes your queries slow down and it's not immediately clear why. Imagine a system that proactively detects performance degradation, analyzes the root cause, and automatically improves your queries and indexes for you—creating pull requests with the exact optimizations needed.

CAST AI is seeking a skilled senior software engineer with expertise in databases and interest in understanding the underlying technology that makes them work. Knowledge of implementation details around transactions, wire protocols, WAL, indexes, query planning, and other fundamental database features will enable you to build a product that automates what's traditionally been manual and complex.

You'll work on a greenfield project with high impact, creating intelligent systems that make database optimization effortless for our customers.

This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.

Requirements:

• Experience working with and troubleshooting PostgreSQL and/or MySQL in production environments
• Experience troubleshooting database-related issues in one of your previous roles—whether as a DBA, backend engineer, SRE, or any position where you've debugged slow queries, optimized indexes, or resolved production database problems
• Strong programming skills in Go and/or C++
• Strong problem-solving skills and the ability to troubleshoot complex issues in a production environment
• Strong written and verbal communication skills in English
• Ability to work independently and collaboratively within a team
• Startup mindset: adaptable, proactive, and comfortable with ambiguity
• A proactive, problem-solving mindset with a "yes we can" attitude

Here are some of the tools we use daily:

• Mostly Golang with C++ in the most critical data pathways
• Extending Envoy with custom network filters
• ClickHouse and PostgreSQL for business metrics
• GRPC and REST APIs
• GitLab CI with ArgoCD as our GitOps CD engine
• Prometheus, Grafana, Loki, and Tempo for observability
• Deployment charts are written in Helm.

Responsibilities:

• Design, build, and operate database optimization services in Go and C++.
• Develop features for query analysis, index recommendations, and automated performance tuning that deliver measurable database cost savings.
• Extend and maintain integrations with PostgreSQL and MySQL protocols, cloud database services (RDS, Cloud SQL, Azure Database).
• Implement query parsing, plan analysis, and recommendation algorithms that identify optimization opportunities.
• Develop monitoring and alerting systems for database performance metrics, connection health, and cost tracking.
• Shape public and internal APIs with an eye for simplicity and developer experience.
• Participate in design reviews, code reviews, and occasional customer deep‑dives.

What’s in it for you?

• Competitive salary (€6,500 - €9,000 gross, depending on the level of experience)
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology.
• Equity options.
• Private health insurance.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

#LI-Remote

Thousands of hotels, resorts, and casinos around the world depend on Duetto’s platform to run their revenue strategy — and you’ll be one of the people making sure it never lets them down. As a Senior DevOps Engineer, you’ll own the infrastructure that powers our global SaaS platform: designing for scale, building for reliability, and driving the kind of security-first culture that keeps us ahead of the curve. If you thrive in complex cloud environments, love solving hard problems, and want your work to have real, tangible impact — this is the role.

What makes us different?

Duetto is the hospitality industry’s leading revenue management platform, founded in 2012 by former Wynn Resorts executives who knew the industry needed better technology. We built the world’s first Revenue & Profit Operating System — a suite of tools (GameChanger, ScoreBoard, BlockBuster, Advance and more) that goes beyond room pricing to give hotels, resorts and casinos a complete picture of their revenue and profitability.

Trusted by clients ranging from independent boutique hotels to global chains, we’ve been named the #1 Revenue Management Software by HotelTechAwards four years running and the #1 Best Place to Work in Hotel Tech in 2025. Backed by GrowthCurve Capital since 2024, we’re accelerating our investment in AI — and we’re genuinely passionate about the industry we serve. We build products we’re proud of, for customers we care about.

What you’ll be doing

• Design and implement robust, scalable AWS infrastructure — supporting key system migrations, platform growth, and the reliability our customers depend on.
• Own the reliability, performance, and security of our production environment: high uptime, rapid incident resolution, and proactive capacity planning.
• Build and maintain CI/CD pipelines, deployment automation, and infrastructure-as-code using Terraform, Terragrunt, and Chef.
• Monitor system health using enterprise observability tools (Prometheus, Grafana, DataDog), defining metrics and response playbooks that get ahead of incidents before they happen.
• Lead security-first practices across the infrastructure estate — proactively addressing vulnerabilities and driving SOC 2 compliance.
• Partner with engineering teams to integrate operational requirements into the development lifecycle and align on architecture decisions.
• Champion AI adoption within DevOps and SRE workflows, evaluating tooling that increases team velocity and reduces toil.
• Respond to on-call incidents with urgency — troubleshoot complex issues, lead detailed root cause analyses, and implement fixes that prevent recurrence.

What we’re looking for

You may be a great fit if you have:

• 5+ years in a DevOps, SRE, or infrastructure engineering role.
• Hands-on AWS experience across IAM, VPC, EC2, ELB, RDS, S3, Lambda, API Gateway, Secrets Manager, KMS, CloudWatch, and CloudTrail — including multi-account management and SSO.
• Proficiency with Terraform for infrastructure-as-code, plus experience with configuration management tools like Chef or Ansible.
• Experience with CI/CD tooling including GitHub, GitHub Actions, JFrog Artifactory, and Jenkins, with familiarity with GitOps methodologies.
• Strong working knowledge of enterprise monitoring platforms — Prometheus, Grafana, or DataDog.
• Solid troubleshooting skills and a track record of leading root cause analyses and implementing durable fixes.
• Proficiency reading Java, Ruby, Bash/Zsh, HCL, Python, and JavaScript.
• Experience with SOC 2 compliance and security-first infrastructure practices.
• Comfort with a weekly on-call rotation.

Strong candidates may also have:

• Experience with container and orchestration technologies — Docker, ECS, or EKS.
• Experience migrating workloads from on-prem or colocation environments to AWS.
• Familiarity with Windows Server, SQL Server, IIS, and .NET environments.
• Experience administering and synchronising MongoDB replica sets.
• Knowledge of ISO 27001, Layer 7 load balancing, or Terragrunt.
• Background in hospitality technology.
• A degree in Computer Science or a related field — or equivalent experience.

Why Duetto?

• Infrastructure that matters — your work directly underpins a platform that hotel operators around the world rely on every day. The stakes are real, and so is the satisfaction.
• AI is how we work — we’re not just talking about AI adoption; we’re actively investing in it across every function, including DevOps. You’ll have space to evaluate and implement tooling that makes a genuine difference.
• A team that moves fast — you’ll report into the Senior DevOps Manager and work alongside engineers who are serious about craft, reliability, and continuous improvement.
• Growth with purpose — backed by GrowthCurve Capital, we’re scaling our platform and our team. There’s a lot being built here, and senior engineers have real influence over how it’s done.
• Come as you are — we’re a diverse, distributed team that values different perspectives and builds inclusively.

The details

Location:  Croatia

Work model:  Remote

Reports to:  Senior DevOps Manager

Duetto is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law.

Sound like you?

We’d love to hear from you — even if you don’t tick every box. Diverse perspectives and non-traditional paths make our team stronger. Apply and let’s talk.

#LI-REMOTE

Senior Fullstack Engineer

If you love building software that actually matters — and you're energised by the idea of shipping production-grade features across the full stack while working in a team where AI is a genuine daily collaborator, not a buzzword — this role is for you. You'll own end-to-end delivery on Duetto's core revenue platform, drive a major migration from monolith to microservices, and help shape how the team engineers at scale.

What Makes Us Different?

Duetto is the hospitality industry's leading revenue management platform, founded in 2012 by former Wynn Resorts executives who knew the industry needed better technology. We built the world's first Revenue & Profit Operating System — a suite of tools (GameChanger, ScoreBoard, BlockBuster, Advance and more) that goes beyond room pricing to give hotels, resorts and casinos a complete picture of their revenue and profitability. Trusted by clients ranging from independent boutique hotels to global chains, we've been named the #1 Revenue Management Software by HotelTechAwards four years running and the #1 Best Place to Work in Hotel Tech in 2025. Backed by GrowthCurve Capital since 2024, we're accelerating our investment in AI — and we're genuinely passionate about the industry we serve. We build products we're proud of, for customers we care about.

What You'll Be Doing

• You'll own full-stack feature delivery end-to-end — from requirements through to production — across Java/Spring Boot microservices and TypeScript/React frontends, including monitoring and troubleshooting in live environments.
• You'll make independent architectural decisions and convert prototypes into scalable, maintainable production systems, collaborating closely with Product, Design, and Engineering to hold a high bar for end-user quality.
• You'll drive the migration of our legacy monolith, applying Domain-Driven Design principles, event-driven architecture patterns, and structured decomposition strategies to modernise software at scale.
• You'll champion test quality by writing automated end-to-end tests in Cypress or Playwright and embedding data-driven testing practices across the team.
• You'll mentor peers on prompt engineering, AI-assisted development, and code review — operating confidently in a generate-and-review model where 50–70% of code is AI-generated.
• You'll contribute to and improve AI-augmented engineering workflows, building and refining custom skills, agents, and agentic pipelines that accelerate the whole team's delivery velocity.

What We're Looking For

You may be a good fit if you have:

• 4–6 years of full-stack engineering experience with production depth across both backend and frontend
• Strong proficiency in Java and Spring Boot for enterprise backend development
• Strong proficiency in TypeScript and React for modern web applications
• Experience building and maintaining GraphQL APIs
• Solid working knowledge of SQL and NoSQL databases, particularly MongoDB
• Hands-on experience with end-to-end testing frameworks — Cypress or Playwright
• A working understanding of microservices architecture and event-driven integration patterns
• Demonstrated experience with Claude Code CLI or a comparable AI code generation tool — you're comfortable in a generate-and-review workflow, not just curious about it

Strong candidates may also have:

• Experience in or exposure to the hospitality technology sector
• A background in legacy modernisation — monolith decomposition, migration planning, or similar
• Familiarity with Domain-Driven Design (DDD) in an enterprise context
• Experience with AI code review tools such as CodeRabbit or Augment
• Working knowledge of AWS, Kubernetes, and CI/CD pipeline management

Why Duetto?

• AI isn't a side project here — it's how we work. With 50–70% of code AI-generated and a team actively building custom agents and agentic pipelines, you'll be operating at the frontier of how software gets built.
• Real architectural ownership. This is a high-autonomy IC role — you'll make independent technical decisions that shape the platform, not just implement tickets.
• Work that ships. We move fast, hold a high bar, and care deeply about what we put in front of customers. If you want to see your work in production, you will.
• A mission worth caring about. Hospitality is a people industry, and we help the people running it do their jobs better. That's something to feel good about.
• Fully remote from Split, Croatia, with a global team that takes collaboration seriously.

The Details

• Location: Split, Croatia
• Work model: Remote

Duetto is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law.

Sound like you?

You don't need to tick every box — if this role excites you and you're strong across most of what we're looking for, we'd love to hear from you. Apply and tell us what you'd bring.

#LI-REMOTE

Staff Software Engineer — Data Platform (Europe)

This is a rare role for an engineer who's genuinely comfortable on both sides of the stack — reading Java Spring Boot services in the morning and writing PySpark pipelines in the afternoon. You'll own the end-to-end data flow that sits behind every pricing decision Duetto makes for thousands of hotels worldwide, bridging our Java core platform and Python data layer while working in an engineering culture where AI is already how the work gets done.

What Makes Us Different?

Duetto is the hospitality industry's leading revenue management platform, founded in 2012 by former Wynn Resorts executives who knew the industry needed better technology. We built the world's first Revenue & Profit Operating System — a suite of tools (GameChanger, ScoreBoard, BlockBuster, Advance and more) that goes beyond room pricing to give hotels, resorts and casinos a complete picture of their revenue and profitability. Trusted by clients ranging from independent boutique hotels to global chains, we've been named the #1 Revenue Management Software by HotelTechAwards four years running and the #1 Best Place to Work in Hotel Tech in 2025. Backed by GrowthCurve Capital since 2024, we're accelerating our investment in AI — and we're genuinely passionate about the industry we serve. We build products we're proud of, for customers we care about.

What You'll Be Doing

• You'll own data pipelines from source to gold — taking data from MongoDB, Kinesis events, RabbitMQ, and PMS/CRS integrations through the full bronze → silver → gold lakehouse architecture, including Iceberg-based ingestion patterns for both batch and near-real-time workloads.
• You'll build connectors and transformations for new data sources — Salesforce, Amadeus, Expedia, and internal platform events — expanding the reach and reliability of the data layer the whole product depends on.
• You'll work across system boundaries: reading Kinesis event schemas and MongoDB data models in the Java platform, then applying that understanding in the Python pipeline codebase — driving schema evolution strategies, data contract enforcement, and backward compatibility across both worlds.
• You'll drive data quality and governance — extending Great Expectations and Data Contract CLI across pipeline tiers, owning Athena views and SQL assets, and building monitoring and alerting for pipeline health, data freshness, and quality drift.
• You'll partner with DevPlatform on event schema design and with data science to operationalise ML workloads, ensuring clean data handoffs across every system boundary.
• You'll work AI-first every day — using Claude Code and MCP tools as a core part of your workflow, contributing to AI-assisted pipeline scaffolding and data discovery tooling alongside a custom multi-agent system built around 17 specialised agents.

What We're Looking For

You may be a good fit if you have:

• 7+ years building production data or backend systems
• Strong proficiency in both Python (PySpark, data engineering) and Java — you can read and navigate Spring/JVM codebases comfortably, not just Python
• Experience with lakehouse or data warehouse architectures on cloud — Iceberg, Delta Lake, Redshift, BigQuery, or Snowflake
• Production experience with AWS data services: Glue, Athena, S3, Lambda
• Experience with workflow orchestration — Airflow, Kestra, Step Functions, or similar
• The ability to work across system boundaries: you understand upstream event schemas, data models, and downstream consumer needs

Strong candidates may also have:

• Hands-on experience with Apache Iceberg — MERGE operations, schema evolution, partition evolution
• Experience with Trino or Presto for federated or interactive SQL analytics at scale
• Experience with dbt for data transformation, modelling, and testing
• Familiarity with data quality frameworks — Great Expectations, Monte Carlo, or similar
• A background in event-driven architectures: Kinesis, Kafka, SQS
• Genuine interest in AI-assisted development and LLM-based engineering workflows
• Familiarity with the hospitality domain or multi-tenant B2B SaaS data challenges

Why Duetto?

• AI-first is the reality, not the roadmap. Every engineer uses Claude Code daily, and you'll be contributing to a custom multi-agent system with 17 specialised agents, human-in-the-loop approval gates, and AI-assisted pipeline generation. This is what modern data engineering looks like.
• Cross-cutting technical ownership. This isn't a siloed data role — you'll operate across Java upstream systems and Python pipelines, with real architectural influence over how data flows through the entire platform.
• The scale and the stakes are real. Millions of pricing decisions processed daily, 80+ integration partners, and a live evolution toward near-real-time streaming. The technical challenges are genuine.
• A team with the right values. Low ego, high EQ, intellectual curiosity, and active mentorship in both directions across a collaborative US and Europe group.
• Modern stack at real scale. Python/PySpark, Apache Iceberg, Airflow, AWS Glue, Terraform, Datadog — tools that matter, used on problems that matter.

The Details

• Location: Croatia (Remote)
• Team: Data Platform
• Direct reports: None
• Travel: None

Duetto is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law.

Sound like you?

You don't need to be an expert in every technology on this list. If you're a strong engineer who spans Java and Python, cares about data quality, and wants to work somewhere AI is genuinely part of how you build — we'd love to hear from you.

#LI-REMOTE

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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.

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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.

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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.

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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.

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.

As a 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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

As a 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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

As a 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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

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)

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

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)

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

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)

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

We’re looking for a Senior Product Manager with a passion for mobile games and a proven track record of creating and delivering engaging, commercially successful gaming content. You’ll own the product vision and roadmap for the Content Creation product area, leading cross-functional game studios to drive growth, retention, and monetisation.

As a senior voice in the product team, you’ll balance player delight with commercial performance - turning insights into actions and ensuring our games remain fun, fresh, competitive, safe and compliant.

What we’re looking for:

• 5+ years of product management experience, with at least 2 years in mobile or iGaming games development.
• Visionary and strategic leader with a hands-on approach, known for ambitious thinking and natural problem-solving.
• Proven track record of leading cross-functional game studios, aligning on goals, timelines, and deliverables.
• Strong analytical mindset, with experience using tools like Tableau, Looker, Amplitude, or similar.
• Deep understanding of game mechanics, player behaviour/psychology, live ops, and engagement strategies.
• Passionate about games - you play them, understand the market, and have sharp insights on what makes a game great.
• Comfortable operating in fast-paced, agile environments.
• Proactive and curious, with strong attention to detail and a willingness to learn.
• Excellent communication skills, able to coordinate across teams and serve as a central point of contact for stakeholders.
• Bonus: Experience scaling game studios, regulatory/compliance, balancing game economies, or launching titles globally.

What you’ll be doing:

• Define and execute the product strategy and roadmap, prioritising high-impact initiatives for in-house gaming content to drive key outcomes and achieve OKRs.
• Own and optimise core KPIs, including DAU, LTV, retention, and monetisation performance.
• Communicate product vision and performance to senior leadership, ensuring cross-departmental alignment and facilitating stakeholder input on the content strategy.
• Lead cross-functional squads - including designers, engineers, QA, artists, and analysts - to deliver games and features that enhance both player experience and commercial outcomes.
• Drive GTM, Live Ops, and marketing initiatives, leveraging high-trust relationships with local market stakeholders to ensure regional relevance and optimal product-market fit.
• Define a hypothesis-driven development process, partnering with Research and Experimentation teams to validate concepts via rigorous data analysis, using multiple research methods, before committing resources.
• Translate user research, data analytics, and market trends into actionable product opportunities and strategic insights.
• Lead the Product Development Lifecycle, acting as a primary escalation point to mitigate risks and remove technical or operational blockers.
• Champion a player-centric culture while maintaining a rigorous focus on achieving overarching business objectives, including active involvement in product UAT.
• Mentor and manage other Product Managers, fostering professional growth and establishing departmental best practices.
• Manage the product backlog and author comprehensive PRDs, ensuring all development work is ruthlessly prioritised based on validated hypotheses, player value, and projected ROI.
• Perform deep-dive performance analysis using SQL (Snowflake) and BI dashboards to identify and execute on-game optimisation opportunities.

About the Role

Superbet is building the future of gaming experiences, and we need a visionary lead to architect our AI-first UX Research Operations function from the ground up. This is a rare opportunity to define how AI transforms research at scale - moving from traditional qual/quant methods to intelligent, automated insight generation that keeps pace with our global expansion. 

You'll be the bridge between cutting-edge AI capabilities and human-centered research excellence, building systems that allow our product teams to make confident, data-informed decisions 10x faster than traditional research allows. 

This is not a traditional ResearchOps role. We're looking for someone who sees AI as the primary research infrastructure, not just a productivity tool. 

You bring methodological mastery, creative curiosity, and the kind of presence that makes participants forget they're being observed and leaders believe you shape company wide narratives. You also bring a future positive mindset: you are actively integrating AI tools into your workflow to do more, faster, without sacrificing the depth that makes qual irreplaceable. You know when AI is helpful and when it is not and can help junior researchers make decisions around when to use them. 

What You Will Build

Year 1: Foundation

• AI Research Infrastructure: Design and implement an AI-native research stack that automates insight synthesis, pattern detection, and continuous discovery 
• Intelligent Repository: Build a living research knowledge base where AI surfaces relevant insights the moment teams need them—no searching through Notion or Dovetail 
• Automated Research Workflows: Deploy AI agents for interview transcription, analysis, synthesis, competitive intelligence, and sentiment monitoring across 12+ markets 
• Research Democratization: Enable product managers, designers, and engineers to self-serve 80% of research questions through AI-assisted tools 

Year 2: Scale 

• Continuous User Understanding: Establish always-on research systems (AI-powered surveys, behavioral analytics, community listening) that generate insights without manual studies Predictive Research: Build models that anticipate user needs, friction points, and opportunities before traditional research would surface them 
• Cross-Market Intelligence: Create AI systems that synthesize insights across Superbet's global markets, detecting regional patterns and universal truths 
• Research Quality Assurance: Implement AI-assisted validation frameworks to ensure insights are reliable, unbiased, and actionable

Year 3: Always On Insights 

• AI predicts user friction points before traditional research surfaces them 
• Cross-market insight synthesis happens automatically 
• Research velocity 10x faster than traditional methods 
• Industry-leading case study: "How Superbet built AI-first research" 

What Success Looks Like 

6 Months:

• - AI research stack operational across 3+ product teams 
• - 50% reduction in time-to-insight for common research questions 
• - Research knowledge base with 100+ synthesized insights, AI-searchable 

12 Months: - Product teams self-serve 70%+ of research needs through AI tools - Continuous user understanding systems running across all markets - Research influences 90%+ of major product decisions 

What We Are Looking For

Basic Experience

• Knowledge of Excel (Pivot Tables, VLookUps) at an advanced level and SQL
• Experience working cross functionally with tech and non-tech teams
• Experience defining program requirements and using data and metrics to determine improvements
• Experience in program or project management
• Experience implementing repeatable processes and driving automation or standardization
• Experience defining and executing program requirements within strict timelines

Essential Experience

ResearchOps Excellence (Critical) - Built research operations from 0→1 at a high-growth company - Designed research repositories, tooling stacks, and democratization programs- Managed research panels, participant recruitment, and compliance frameworks- Scaled research to support 50+ stakeholders across multiple product teams AI & Research Intersection (Critical) 

• - 5+ years in UX Research, with 2+ years actively using AI in research workflows
• - Shipped AI-powered research tools, processes, or platforms (not just "used ChatGPT") 
• - Deep understanding of LLMs, RAG systems, prompt engineering for research applications 
• - Experience evaluating AI research tools and building AI-augmented research practices 
• Technical Acumen (Critical) 
• - Comfortable reading code, writing SQL, or working with APIs 
• - Built custom AI workflows (GPT API, Claude API, Zapier, Make) 

Industry Context (Preferred) - Experience in regulated industries (gambling, fintech, healthcare)- Multi-market or international research experience - Background in high-velocity product environments (weekly releases) 

Skills & Mindset

• World-class operator: You have a gift for going across the organization to find the most optimal ways of work - time, money, resource wise.
• AI-enhanced, not AI-dependent: You use AI to go faster and deeper, but your analytical judgement is irreplaceable and you know it. You apply AI tools critically, not uncritically.
• Meticulous planner: You are an expert in Operations and constantly keep improving the team’s delivery model.  
• Org Mover: Your research is not theory alone, you know how to make things tangible, bite sized and move people and work forward. 
• Embrace difficult conversations - Driving research impact is as much about doing good research as it is about convincing people to see things your way. You work with people both easy and difficult to collaborate with to make great experiences come alive. 
• Frugal: You continuously improve our spending habits and drive financial efficiency for the org. 

Nice to Have

• Experience in high intensity consumer products, marketplaces, gaming, financial services, with some degree of experience in trust and safety is useful. 
• Experience in launching new programs, markets and changing large scale work processes in short turn around.
• Experience in some European languages. 

Why This Role at Superbet

Sports is one of the richest contexts for qualitative research: the experience is emotionally intense, socially embedded, culturally specific, and morally complex. Users have contradictory motivations. Their stated and actual behaviour diverge. The moments of joy and frustration are extreme. Understanding all of this deeply, not just what users click, but why they feel what they feel - is what separates good product decisions from great ones.

• Access to a diverse, passionate user base across 12+ markets - every cultural context brings new research challenges.
• A team that values qualitative rigour and won't ask you to reduce everything to a number.
• Senior visibility: your insights will be read by the CPO and product leadership, not just deposited in a repo.
• A Principal Quant Researcher as a genuine peer - someone to build with, argue with, and create better mixed-methods evidence with.
• Competitive compensation at Staff IC level with equity and a genuine investment in your development as a researcher.