Here’s a 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. 

Here’s 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. 

Here’s a breakdown of 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. 

These are the essentials you’ll need to get 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. 

 

It would be great if you had these too, but we’ll support you if you don’t: 

 

• 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. 

Here’s where this role goes next: 

 
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. 

  #LIHybrid