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Diligent

Product Operations Manager

London
Posted about 16 hours ago
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Summary of the Role

Data is only powerful when everyone agrees what it means.

We’re revamping how we measure success and end user value delivery across our portfolio of products, and this role sits at the centre of it — the person who makes one number mean the same thing in every room, the person who builds the data foundations that drive actionable behavioural insights.

As our Lead for Product Data & Telemetry, you’ll design the single source of truth for how we measure our products: the metric definitions, the telemetry standards and the governance model that every dashboard, business review and roadmap is built on.

You’ll define the data contract that engineering teams instrument against, and build the models that turn raw product telemetry into portfolio-level insight — with federated data governance as the operating principle rather than an afterthought.

AWS/Snowflake is our warehouse spine. The capture and BI layers are open decisions and you will help make them, so you are joining early enough to choose the tools rather than inherit them.

The work has a short route to the top. Your models feed the monthly and quarterly business reviews that our executive team, our CTO and our investors use to run the portfolio. Not many roles at this level sit that close to the decisions.

This is sponsored at executive level, and engineering teams will instrument against the contract you define. You will not be writing standards into a vacuum.

This is a hands-on senior individual-contributor role for someone who thinks in schemas, metrics, definitions and governance — you can write clean SQL, design an event schema, and hold a standard across teams you don’t manage.

The ambition is world class: a governed telemetry and product-analytics capability strong enough to run a 30-product portfolio on, and you are at the centre of building it.

You’ll sit at the centre of the Product Operations function, working shoulder to shoulder with product, engineering, data and analytics leaders — and your work will shape how the company sees its own products.

What Your First Twelve Months Should Look Like

  • First 90 days. Learn the estate and meet the engineers who instrument it. Agree the measurement model for one product end to end and put a defensible adoption number in front of the business. One narrow, visible win before we scale anything.
  • Three to six months. Data contract published, instrumentation specification landed with engineering, and the first business unit building against it. Definitions, naming and change control in place and governed.
  • Six to twelve months. The model rolling out across the remaining business units through the BU-aligned analysts, portfolio adoption and value reporting running on your numbers, and the tooling decisions made and implemented.

What You’ll Do (Not All of It, Just the Important Stuff)

  • Partner with our data governance and enterprise architecture teams on the product, customer and user taxonomies — making sure they are clear, and that product telemetry is modelled and segmented against a single agreed source of truth rather than local variants.
  • Own the product measurement standard — canonical metric definitions, naming conventions, field ownership and change control, applied consistently across every business unit.
  • Write the instrumentation specification that engineering teams build against, and partner with them to land telemetry against the data contract.
  • Build the analytics and data models — SQL, BI and roll-up logic — that turn product telemetry into portfolio-level insight on adoption and value.
  • Own data quality assurance: coverage, freshness and reconciliation, so monthly and quarterly business reviews run on measurement with known provenance.
  • Set the technical standard for a team of BU-aligned analysts, acting as their reference point as they roll the standards out across the business.
  • Help shape the direction of our product analytics stack as we revamp it — capture, warehouse and BI — so the measurement model and the tooling are designed together rather than bolted on.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Essentials for an Interview

  • Proven experience designing and governing product data models and taxonomies — you’ve taken canonical metrics and naming standards into a complex, multi-product estate and made them stick.
  • Strong data governance practice: schema and field ownership, change control, and a track record of driving standards adoption across teams you don’t own.
  • Fluency in SQL and the BI / data-warehouse layer — you can build and validate roll-up logic yourself.
  • Enough data-engineering literacy to design event and telemetry schemas (Pendo, Amplitude, Segment or similar) and write an instrumentation spec engineers respect.
  • Experience standing up a data contract, taxonomy or metrics layer in a product or analytics context, ideally B2B SaaS — including the reality of bringing acquired products onto a shared measurement model.
  • The credibility to influence without authority — you can hold a standard with engineering and product teams you don’t line-manage.
  • A collaborative, pragmatic style and a bias for making things clear, simple and usable for the people who rely on your data.

Nice to Have

  • Experience with the modern product-ops tool stack — Salesforce, Jira Product Discovery, Pendo — and with consolidating fragmented tooling into a single system of record.
  • Exposure to product value / ROI measurement — connecting product usage to customer and commercial outcomes.
  • Familiarity with GRC, governance or regulated-software domains.
  • A track record of building data capabilities from the ground up in a scaling business.

Next Steps

We are building this function, not maintaining it. You set the technical standard that the BU-aligned analysts land across the business, which means technical leadership from day one without waiting for a management line.

As the function grows, the routes from here are principal-level ownership of product data across Diligent, or leading the team that runs it. We would rather be straight with you about that than promise a title we cannot yet name. The scope is real, and it is expanding.

About Us

Diligent is the AI leader in governance, risk and compliance (GRC) SaaS solutions, helping more than 1 million users and 700,000 board members to clarify risk and elevate governance. The Diligent One Platform gives practitioners, the C-Suite and the board a consolidated view of their entire GRC practice so they can more effectively manage risk, build greater resilience and make better decisions, faster.

At Diligent, we're building the future with people who think boldly and move fast. Whether you're designing systems that leverage large language models or part of a team reimaging workflows with AI, you'll help us unlock entirely new ways of working and thinking. Curiosity is in our DNA, we look for individuals willing to ask the big questions and experiment fearlessly - those who embrace change not as a challenge, but as an opportunity. The future belongs to those who keep learning, and we are building it together. At Diligent, you’re not just building the future - you’re an agent of positive change, joining a global community on a mission to make an impact.

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Learn more at diligent.com or follow us on LinkedIn and Facebook

What Diligent Offers You

  • Creativity is ingrained in our culture. We are innovative collaborators by nature. We thrive in exploring how things can be differently both in our internal processes and to help our clients
  • We care about our people. Diligent offers a flexible work environment, global days of service, comprehensive health benefits, meeting free days, generous time off policy and wellness programs to name a few
  • We have teams all over the world. We may be headquartered in New York City, but we have office hubs in Washington D.C., Vancouver, London, Galway, Budapest, Munich, Bengaluru, Singapore, and Sydney.
  • Diversity is important to us. Growing, maintaining and promoting a diverse team is a top priority for us. We foster and encourage diversity through our Employee Resource Groups and provide access to resources and education to support the education of our team, facilitate dialogue, and foster understanding.

Diligent created the modern governance movement. Our world-changing idea is to empower leaders with the technology, insights and connections they need to drive greater impact and accountability – to lead with purpose. Our employees are passionate, smart, and creative people who not only want to help build the software company of the future, but who want to make the world a more sustainable, equitable and better place.

Headquartered in New York, Diligent has offices in Washington D.C., London, Galway, Budapest, Vancouver, Bengaluru, Munich, Singapore and Sydney. To foster strong collaboration and connection, this role will follow a hybrid work model. If you are within a commuting distance to one of our Diligent office locations, you will be expected to work onsite at least 50% of the time. We believe that in-person engagement helps drive innovation, teamwork, and a strong sense of community.

We are a drug free workplace. Diligent is proud to be an equal opportunity employer. We do not discriminate based on race, color, religious creed, sex, national origin, ancestry, citizenship status, pregnancy, childbirth, physical disability, mental disability, age, military status, protected veteran status, marital status, registered domestic partner or civil union status, gender (including sex stereotyping and gender identity or expression), medical condition (including, but not limited to, cancer related or HIV/AIDS related), genetic information, or sexual orientation in accordance with applicable federal, state and local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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Skills

SQL
Data Governance
Product Telemetry
Data Modeling
Schema Design
B2B SaaS
Product Analytics
Instrumentation Specification
Stakeholder Management
Data Quality Assurance
BI Tooling
Taxonomy Design

Location

London, England, United Kingdom

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