Product Owner - Data Processing
New
M
MOIA GmbHMobility Tech
Outside Germany for up to 6 weeks per year from over 35 countriesFull-TimeMiddle
Salary not disclosed
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Job Details
- Languages
- English
- Required Skills
- AWSDevOps
Requirements
- Proven experience as a Product Owner or Product Manager working closely with engineering teams, turning high-level objectives and PI goals into clear, well-structured backlog items that enable predictable delivery.
- Track record of outcome-oriented product ownership, not just backlog management.
- Curiosity to grow your PM craft and share learnings across the product organization.
- Strong understanding of data processing concepts, especially time-series, sensor data, and related data quality challenges.
- Experience with schema evolution, data normalization, validation, and maintaining shared outputs for multiple downstream consumers.
- Structured problem‑solving skills and the ability to translate ambiguity into actionable backlog.
- Experience working in cloud-based data platforms and managing teams who practice continuous delivery and DevOps.
- Confident communicator who enjoys working across technical and non-technical stakeholders in a scaled agile environment; communicating with them fluently in English (German is a plus).
- Proven track record in stakeholder and supplier management, including hands-on experience working with external development partners.
- Ability to drive alignment across internal teams and suppliers while managing dependencies, risks, and delivery commitments.
- Pragmatic mindset: ability to turn ambiguity into action, balance short-term delivery with long-term maintainability.
Responsibilities
- Own the product scope and backlog for a data processing capability that ingests raw multimodal sensor data from vehicles and third‑party providers via AWS.
- Drive the implementation of strict input normalization, temporal alignment and synchronization, de‑duplication and signal merging, schema validation and version handling.
- Ensure stable, backward-compatible output formats so upstream changes do not disrupt downstream consumers or workflows.
- Prioritize and manage your team’s backlog in alignment with Program Increment (PI) objectives and overall product goals within a SAFe environment.
- Work closely with Product Management and other Product Owners in the Agile Release Train to align priorities, dependencies, risks, trade-offs, and delivery.
- Act as the main interface between data producers (e.g. OEMs, SDS provider) and downstream engineering teams, translating consumer needs into concrete features and quality criteria.
- Manage dependencies, risks, and trade‑offs transparently across stakeholders.
- Ensure backlog readiness and active participation in ceremonies such as PI Planning, backlog refinement, and Inspect & Adapt events.
- Define the product vision for Data Processing and own measurable outcomes.
- Co-lead the team in the Triangle with Tech Lead and Agilist; influence and align without authority.
- Prioritize based on evidence: usage data, quality metrics, and consumer feedback.
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