[C3I] Product Manager/Technical Product Owner (Data Platform & AI Readiness)

Software Mind

3d•Hybrid

About The Position

We are looking for a technically oriented Product Manager / Technical Product Owner who will co-own the development of a modern data platform enabling analytics, AI, and machine learning use cases. This role is hands-on and requires understanding of data architecture, data engineering practices, and platform design. You will work closely with Data Engineers, Architects, and ML teams to shape a scalable, reliable, and production-ready data ecosystem. The ideal candidate has a technically hands-on mindset, can communicate effectively between engineering and product teams, is interested in building data platforms, and is comfortable working closely with architecture and implementation topics.

Requirements

6 + years of overall experience
min. 2 years in data architecture / data engineering / platform design
Practical understanding of modern data architectures (Lakehouse, DWH, streaming)
Practical understanding of cloud platforms (AWS / Azure / GCP – at least one)
Practical understanding of data processing tools (e.g. Spark, dbt, Airflow or similar)
Experience working closely with engineering teams (Data / Backend / Platform)
Ability to understand and discuss data models, schemas, pipelines, performance topics, and trade-offs between scalability, cost, and complexity
Basic understanding of ML ecosystem (pipelines, model lifecycle, deployment concepts)
Strong analytical thinking and problem-solving skills
Good communication and stakeholder management skills
AgilePM Practitioner certification or equivalent
Scrum Product Owner II (PSPO II) or equivalent
Working knowledge of PMBOK (project management standards and practices)

Nice To Haves

Experience in regulated industries (finance, telco, media, healthcare)
Exposure to MLOps / Feature Stores / Data Governance
Background as Data Engineer, BI Engineer, or Technical Analyst
PMP certification

Responsibilities

Co-define and evolve the data platform roadmap in collaboration with architecture and engineering teams
Translate technical and business requirements into epics, user stories, and technical backlog items
Work closely with Data Engineers and Architects on data models and architectures (batch/streaming), data pipelines and ingestion frameworks, and storage (e.g. data lake / data warehouse) and processing layers
Support design and implementation of platform components for machine learning workflows (MLOps, feature stores, model lifecycle) and data observability, lineage, and quality monitoring
Ensure datasets are reliable, well-structured, and ready for analytics and ML use cases
Participate in technical discussions and architecture decisions
Drive delivery in an agile setup (planning, backlog refinement, prioritisation)
Communicate technical concepts in a clear way to non-technical stakeholders