Data Product Owner

Would you like to shape the technical foundation of AI & Advanced Analytics products — and work at the intersection of solutions architecture, data products, and business impact?

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What is the position about?

We are looking for a Data Product Owner to join our Product team at a pivotal moment in our offers. This role sits at the heart of how we conceive, architect, and continuously evolve the AI products we deliver to our clients.

You will be the technical and conceptual bridge between client needs and delivery. When a client brings a problem, you will be the person who translates it into a robust, scalable solution — defining data architecture, data engineering pipelines, and the interplay between the solution's components (frontend, backend, databases, run manager, dashboards, customer infrastructure, etc.). You are comfortable going deep on technical design while also communicating with clarity to business stakeholders.

A central part of this role is co-owning our modular delivery platform - AIR. It's a shared infrastructure used across multiple teams and directly by our clients to deploy analytical and AI models. You will work closely with our software engineering team to evolve this platform, ensure it meets the growing demands of our projects, and drive decisions that improve its modularity, reliability, and usability.

This is a role for someone who wants to build things that matter, with lasting technical impact across the company.

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What will you be doing in your day-to-day?

• Act as solutions engineer during the pre-sales and project scoping phases, translating client requirements into end-to-end technical blueprints — from data sources and ingestion pipelines to model integration and front-end interfaces optimized for AI.
• Define and document data architecture decisions: database design, data engineering flows, API contracts, and the integration logic between AI models and product layers.
• Own the product roadmap and backlog of AIR, working alongside software engineers and business teams to prioritise features, improvements, and technical debt.
• Collaborate with data scientists, engineers, and consultants to ensure that AI models are deployed in a way that is performant, maintainable, and aligned with client expectations.
• Lead technical discussions with clients and internal stakeholders, making complex architectural trade-offs accessible and actionable for non-technical audiences.
• Identify reuse opportunities across projects, promoting platform components and patterns that reduce delivery time and improve consistency.
• Contribute to engineering standards, documentation, and the continuous improvement of how we design and ship AI products.

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Your first 9 months

We want to set you up for success. Here is what the journey looks like.

Months 1 to 3 - Learn the landscape

• Immerse yourself in LTPlabs — our clients, culture, and ways of working
• Shadow senior colleagues across delivery and solutions engineering
• Develop a thorough understanding of AIR and how it is used across projects

Months 4 to 6 - Start contributing

• Take on backlog management for AIR — write requirements and guide the software team, with support from senior colleagues
• Design end-to-end solutions for smaller, well-scoped projects with increasing autonomy
• Begin owning technical conversations with internal teams

Months 7 to 9 - Build independently

• Operate with confidence across backlog ownership and solution design
• Propose and shape new ideas for AIR's evolution
• Architect more complex solutions involving third-party integrations, with guidance from senior colleagues

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Who are you?

• 4–5+ years of experience in roles involving data products, solutions engineering, or technical product ownership — with hands-on exposure to forecasting, optimisation, AI, or advanced analytics solutions.
• Strong ability to architect end-to-end solutions: you can look at a set of requirements and define the databases, pipelines, APIs, and interfaces that will bring them to life.
• Solid understanding of data engineering concepts — ETL/ELT pipelines, data modelling, warehouse design — and how they underpin reliable analytical products.
• Familiarity with front-end/back-end integration patterns, API design, and the technical considerations of deploying ML or analytical models into production environments.
• Experience working alongside software engineering teams, with the ability to translate product vision into concrete technical specifications and to manage a product backlog.
• A structured, ownership-driven mindset — you take responsibility for technical outcomes and are comfortable making decisions under ambiguity.
• Excellent communication skills in Portuguese and English, with the ability to engage both technical teams and business stakeholders with clarity and confidence.

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Nice to have

We don't expect you to tick every box — but candidates with any of the following will stand out.

On the technology side:

• Familiarity with workflow automation tools such as Argo Workflows or ArgoCD, N8N, Kestra.
• Authentication protocols like OAuth, SSO (Azure AD), and JWT.
• Experience designing or consuming REST APIs.
• Candidates who have worked with large SQL or NoSQL databases — particularly PostgreSQL or Redshift — or with Databricks and data engineering pipelines will also be valued.
• Exposure to observability and logging tools (Grafana, Prometheus, Loki)
• Kubernetes clusters, AWS-based cloud environments, and networking fundamentals such as VPN and DNS configuration rounds out the technical picture.
• Experience managing dev environments and backup strategies is equally welcome.

On the industry side, we work extensively with clients in consumer goods, retail, and manufacturing — so prior exposure to domains such as supply chain planning, sales performance, personalized marketing, or demand forecasting is a meaningful advantage.

What do we offer?

• Flexible scheduling with a remote option
• Annual bonus
• Health insurance plan
• Extra vacation days
• Personalised career development plan
• Telecommunications plan & smartphone budget
• Vibrant office with snacks, fruit & coffee
• Social calendar: dinners, sports & beer Fridays

Equal opportunities

At LTPlabs, we are committed to creating a diverse and inclusive workplace. We strongly encourage people from all backgrounds, ways of thinking, and working to apply — regardless of race, disability, age, gender identity, sexual orientation, or religion.

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