Plentific
Senior Product Manager - Data and Insights
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About Us
Plentific is a property technology platform used by housing providers, local authorities, housing associations, asset managers, and contractors across the UK and Germany to coordinate repairs, maintenance, and contractor workflows at scale. The platform combines a marketplace, workflow automation, and operational analytics, and is built to handle the volume and compliance demands of social housing, local authority property portfolios, and large-scale residential operations.
We are headquartered in London, with engineering and operations across the UK and Germany. Our investors include Highland Europe, Brookfield, Mubadala, RXR Digital Ventures, and Target Global.
We are growing the team to expand the platform's coverage across Europe and to integrate AI throughout the product and operating model. If you are interested in working on hard, real-world problems in a sector that has long been under-served by good software, we would like to hear from you.
The Role
Every repair, appointment, compliance certificate and invoice on the platform leaves data behind. We are hiring a Senior Product Manager, Data and Insights to own what we do with it. The remit covers the whole chain: the data model, pipelines and warehouse underneath, the reporting our clients use to run their portfolios, the datasets behind our AI features, and the features that act on what the data shows. That last part matters most. You will be measured on what changes as a result of the data, not on what it reports.
You will sit in the Product team and report to the Head of Product. You will work most closely with data engineering, analytics and data science, and with the product managers who own repairs, compliance and contractors. You will also spend time with the client-facing and operations teams, who work with this data daily and hear directly from clients about it. We expect you to use AI in your own work: prototyping with agentic tools, writing specs engineers can build from, testing model output against a real eval set, and knowing when a person needs to stay in the loop.
Key Responsibilities
Product Strategy and Commercial Ownership
- Own the direction and strategy for Plentific's data and insight products, from the internal data model through to what clients see.
- Align the data roadmap with Plentific's AI roadmap and commercial goals, judging each investment on the operational and financial return it earns.
- Grow the commercial value of data inside existing client relationships, through analytics tiers, data services and APIs for the housing providers and local authorities we already serve.
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Client-Facing Analytics and Insight to Action
- Define the compliance, repairs performance and spend reporting that client organisations depend on to run their portfolios.
- Identify where predictive models turn years of historical maintenance data into a forecast someone can act on.
- Ship platform features that act on the insight, and hold them to the outcomes they were meant to shift.
- Translate what stakeholders ask for into specific data product features with measurable success criteria, and decline the requests that do not earn their place.
Data Foundations, Quality and AI
- Set the standards for data quality, lineage and access across pipelines and the warehouse, and hold the platform to them under UK GDPR.
- Own the data behind Plentific's AI features: training and evaluation datasets, model inputs, benchmarking, and human-in-the-loop feedback loops.
- Partner with the AI team so that our AI products can access the right data with the semantic definitions and context needed to interpret it correctly.
- Own each data product end-to-end, from discovery through to launch and iteration, with data engineers, analysts, data scientists, designers and other product managers.
Requirements
- Strong command of the modern data stack, including warehouses such as Snowflake, BigQuery or Databricks, transformation in dbt or an equivalent, the trade-offs between ETL and ELT, and the unit economics that govern both, from warehouse compute to ingestion pricing models.
- Direct experience with BI and serving tools such as Looker, Power BI, Tableau, Metabase or Hex, and the judgement to decide what belongs in the semantic layer rather than in individual reports.
- Hands-on background in the data domain, including pipelines built or managed first-hand and enough SQL to interrogate the warehouse without waiting on an analyst.
- Fluency in dimensional modelling and semantic layers, from defining a metric once and holding the organisation to that definition, through to reviewing data model designs, layering conventions and API contracts with engineers.
- Practical grasp of data quality engineering, including testing, lineage, freshness monitoring, and the design of data contracts between producers and consumers.
- Working knowledge of evaluation for machine learning features, including held-out eval sets, error asymmetry, confidence thresholds, drift monitoring in production, and the design of human-in-the-loop controls.
- Sound understanding of UK GDPR as it applies to product decisions, including lawful basis, purpose limitation, special category data, and the aggregation thresholds that make cross-client analysis defensible.
- Excellent written, verbal and presentation skills, including the ability to simplify a complex idea for a non-technical audience and to stay straight with people when the news is bad.
- A bias for action, with the appetite to lead a change in how the organisation uses data and to run the day-to-day detail that gets it there.
- Comfort working where the data model, the client requirement and the priority are all still moving, and the resilience to keep a team pointed at the outcome while they settle.
- High ambition, with the urgency to deliver a large roadmap at pace using AI and a positive, can-do attitude.
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Experience And Qualifications
- 8+ years of product management experience, including substantial time in technical product management on data, analytics or platform products.
- Demonstrable track record of shipping data and analytics-intensive products with measurable business results.
- Experience working alongside data engineering, analytics and data science teams as their product counterpart.
- Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, Information Systems, or a related quantitative field, or equivalent practical experience.
- Located in London and able to work from our London office on a hybrid basis.
- Right to work in the United Kingdom.
Benefits
We offer:
- A competitive compensation package
- 25 days annual holiday, plus one additional day for every year served, up to a maximum of 5 additional days
- Flexible working environment, including the option to work abroad
- Private healthcare for you and your immediate family, with discounted gym membership and access to optical, dental, and private GP services
- Enhanced parental leave
- Life insurance at 4× salary
- Employee assistance programme
- Company volunteering day and charity salary-sacrifice scheme
- Learning management system powered by Udemy
- Referral bonus and charity donation when someone you introduce joins the company
- Season ticket loan, Cycle to Work, electric vehicle, and Techscheme programmes
- Pension scheme
- Company-sponsored lunches, dinners, and social gatherings
- Fully stocked kitchen with drinks, snacks, fruit, and breakfast cereals
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