levari

The opportunity

Love the space where business questions meet hands-on data work? You'll work across a portfolio of fast-growing software companies backed by a private equity investor, building the revenue reporting their founders and finance leaders rely on — one company at a time. A rare chance to sit close to the top of the business, learn how SaaS companies really make money, and grow fast at the intersection of commercial and technical.

This could be a great fit if you're…

• From QA or data quality — you love making data clean, accurate and trustworthy. Reconciliation and getting the numbers right are at the heart of this role.
• A Product Owner / Manager in SaaS or FinTech — you already know the metrics and the stakeholders, and you want to go deeper and more hands-on with the data itself.
• A Business / Data Analyst or RevOps person — ready to step up into real ownership of commercial reporting.
• Comfortable at the intersection of business and technical — and you want to make that your core role, not a side skill.

What you'll do

• Build clear, unified commercial reporting from the ground up for one company at a time — starting with ARR and “snowball” analytics (new, upsell, downsell, churn).
• Pull data together from different systems (billing, CRM, contracts, finance), clean and reconcile it, and turn it into one trusted source of truth. Getting it accurate is the whole point.
• Work out who to talk to and where the answers live; partner directly with each company's finance/commercial leaders and data team.
• Once it's built and trusted, hand it over and take on the next company.

What you bring (core)

• Business × technical. You’re equally happy in a commercial conversation and in the data. This matters most.
• Hands-on builder. Proficient in Python and SQL — able to take raw source data through to clean, validated output tables and reporting cubes, working fairly independently. Everything around the core can be handled pragmatically, including with AI.
• Commercial curiosity. A fast grip on how businesses make money; comfortable translating business questions into a technical implementation. SaaS metrics exposure is a plus, and you’re keen to master them.
• Sharp and accurate. Detail-driven, with the confidence to ask good questions and explain your numbers clearly.

The ideal profile we’re targeting (a plus, not all required)

• Commercially oriented. Ideally 2+ years in a consulting, advisory or deal-support environment (e.g. Big 4 or a boutique analytics consultancy), used to turning business questions into practical data solutions.
• System & data migration. Experience with ERP, CRM or billing platform migrations (e.g. Salesforce, NetSuite, Chargebee) — understanding the data-quality pitfalls (duplicate customers, broken historical linkages) and how to reconcile pre- vs. post-migration data to keep the numbers continuous.
• Accounting or SaaS exposure. Either an accountant by trade, or someone with SaaS revenue-analytics exposure — familiar with subscription metrics (ARR, NRR, churn), snowballs and billings-to-revenue reconciliations.
• Handy to have. Familiarity with platforms like Databricks, Azure or GCP, and with project management across stakeholders.

Why you’ll like it · Engagement

• Exposure across many fast-growing software businesses with a direct line to their leadership — real ownership, and a fresh challenge every few months.
• Interim / contract, full-time capacity. Back-to-back projects (~3 months to a year each). Fully remote, occasional optional travel. Mentored by an experienced data leader. Start soon.

Role Overview

We are looking for a highly experienced consultant to act as a trusted technical advisor on a part-time basis. You will review our client's overall technical setup, assess security implications, evaluate architectural decisions, and provide continuous guidance on improving both the product and the development environment - with a particular focus on the growing use of AI in the development process.

Engagement

• Scope: ~10-20 hours per month
• Start: Within the next 1-2 months
• Duration: Long-term collaboration, with possible extension of hours

Mode: Remote / part-time advisory

Responsibilities

• Review the overall technical setup and provide strategic, hands-on advice
• Assess security posture and identify risks across the stack
• Evaluate architectural decisions and recommend improvements
• Advise on the safe and effective integration of AI into development workflows

Support continuous improvement of the product and the development environment

Required Profile

• Senior-level expertise in software architecture and security
• Strong experience with AI-assisted development (tools, workflows, and their security/quality implications)
• Ability to act as a strategic advisor and communicate clearly with the team
• Broad technical judgment across modern web, backend, and mobile stacks

Deep hands-on proficiency in every language below is not required. Architecture, security, and AI-development expertise are the priority; the candidate should be able to reason confidently across these technologies.

Technical Environment

• Backend: Java, Spring Boot, PostgreSQL
• Frontend: React, TypeScript
• Mobile: Native Android (Kotlin)
• Streaming: Custom IPTV server converting satellite input into other streaming formats

New service: Go with PostgreSQL (in development)

About the role

Our client is private equity investor backing growth-stage software companies. Their portfolio companies have strong product-market fit but, being young, lack consistent commercial KPI definitions — so there is no clear, comparable view of performance. This hands-on interim role brings standardized, board-grade commercial reporting into these companies one at a time, starting with ARR and "snowball" analytics, until the reporting is built, trusted, and handed over.

What you'll do

• One company at a time. Embed with a portfolio company and take it through the data maturity curve; each company is a discrete project, worked back-to-back with the next.
• Build the numbers. Create unified commercial reporting from the ground up, starting with ARR and snowball analysis (New, Upsell, Downsell, Churn) to give leadership an accurate view of performance.
• Find the truth. Work out who to ask and where the data lives; partner directly with the CFO or C-1 level and the company's data team where one exists.
• Get it right. Pull together, clean and reconcile data from disparate systems (billing, general ledger, contracts, CRM) into a single source of truth reconciled to the finance ledger — accuracy is the most important outcome.
• Hand over. Once built and validated, transfer ownership to the portfolio company and move to the next project.

What we expect

• Finance & data expertise. Deep expertise in finance and in data and its analysis — able to stand behind your numbers and push back with C-level stakeholders on the strength of that expertise.
• SaaS metrics fluency. Confident with ARR, NRR, churn, snowballs and billings-to-revenue reconciliation.
• Business x technical. Genuinely comfortable at the intersection of business and technical — equally at ease with a commercial conversation and a hands-on build. This matters most; it is not a pure data-engineering role.
• Hands-on delivery. Able to build analyses end-to-end on a modern data stack — Python and SQL, in environments such as Databricks, Azure or GCP — working independently across companies with or without their own data teams. Tooling around the core can be handled pragmatically, including with AI.

Engagement details

• Format. Interim contract, full-time capacity; back-to-back projects across the portfolio. Individual projects run from ~3 months to over a year depending on size and complexity.
• Location. Fully remote. Occasional travel (a few days per month) is welcome but not a hard requirement. Some companies may provide their own device.
• Team & growth. First of several sequential hires as the portfolio scales. Start ASAP; a ramp-up curve is expected.