Founded in 2020, unybrands is the next-generation brand accelerator platform built to acquire, integrate, and scale digital-first consumer brands. Headquartered in Miami, with offices in New York, London, Berlin, and Shenzhen, our 240+ team brings deep expertise across e-commerce, brand management, consumer retail, operational scaling, and M&A.
Since inception, we have acquired 30+ brands across Pet Care, Personal Care, Home Care, Supplements, Baby & Juvenile, Garden & Outdoor, Sports & Fitness, and Home & Lifestyle — completing 20+ acquisitions and delivering 16 consecutive quarters of like-for-like organic growth post-integration.
Our competitive advantage lies in a fully integrated operating system purpose-built to transform digital brands into omni-channel category leaders. Powered by a proprietary technology stack built on NetSuite ERP with 200+ data integrations, our platform enables brands to thrive across marketplaces, direct-to-consumer channels, and brick-and-mortar retail.
We focus on acquiring digital-first brands within carefully selected verticals, then applying tailored value creation playbooks that drive growth through innovation, expansion, and automation. We believe the next generation of consumer brands will be built differently — and we're building the AI-enabled retail tech platform to help them consolidate and win.
About the Role
We are looking for a Finance Data & Systems Lead to join our Strategic Finance team at unybrands. The position reports to the Director of Strategic Finance and owns the integrity of the data our finance function runs on - from source systems such as Amazon Seller Central and NetSuite, through our connectors and pipelines, into our BigQuery data warehouse — as well as the continuous improvement of our finance systems and processes.
unybrands runs a multi-entity, multi-currency business across the US, UK, Canada, and the EU, selling through Amazon, Shopify DTC, TikTok Shop, Walmart, and retail partners. Today, the data behind that business is spread across many systems, slow to come together, and has to be checked by hand before a report can be trusted. That doesn't scale. Your mission is to change it: working hand in hand with the Data & Technology team, Finance, FP&A, and Operations, you will make sure every number we build on is validated, reconciled, and correct - so that the figures we put in front of our CEO, board, and investors stand up to any question.
This is a dedicated, full-time mandate. Today no one owns this problem day to day: our Accounting and FP&A teams are fully occupied with close, reporting, and presentations, and IT is focused on its own roadmap. You will not be working alone - you will have business partners in Accounting/NetSuite, IT, and FP&A - but you will be the person driving data integrity forward every single day.
This is a foundational, ongoing role - not a one-off clean-up. As we keep acquiring brands, new data sources and gaps will keep appearing, and you will own finance data as a living product. Clean, trusted data and well-run systems are what will allow us to implement AI and agents across Finance and FP&A, automate reporting, and scale the finance function as the portfolio grows.
This is a senior individual-contributor role with room to grow: as the work scales, we expect it to develop into a finance data and automation team. You will bring a hands-on, builder mindset - as comfortable tracing a broken connector, writing a SQL reconciliation, or fixing a data model yourself as you are walking a stakeholder through what went wrong and agreeing how to stop it happening again.
Key Responsibilities
Data Integrity & Validation
- Own end-to-end validation of finance data: reconcile Amazon Seller Central and other marketplace data against NetSuite, inventory records against 3PL and warehouse data, and NetSuite against BigQuery.
- Confirm that data pipelines and connectors (marketplaces, order management, 3PL, banking, spend management) are complete, timely, and correctly mapped.
- Build automated checks, reconciliations, and exception reports so issues are caught before they reach a report - not in a leadership meeting.
- Investigate breaks and run root-cause analysis; fix bugs and connector issues directly where you can, and drive the fix with the owning team or vendor where you can't.
Trusted, Ready-to-Use Data Sets
- Produce cleansed, validated, and documented data sets - sales, margin, inventory, cash - that anyone in the business can use with confidence.
- Establish clear data definitions, ownership, and sign-off so Finance, FP&A, and leadership all work from one version of the truth.
- Make sure the numbers presented to the CEO, board, investors, and lenders are reconciled and defensible.
Stakeholder Partnership & Issue Resolution
- Be the dedicated owner of finance data integrity, working with your business partners in Accounting/NetSuite, IT, and FP&A - and with Operations and brand teams - to prioritise issues and agree who fixes what.
- Explain data problems clearly - what is wrong, what it affects, and what needs to change - and push owners through to resolution.
- Track open issues and communicate progress, risks, and impact through regular updates.
Finance Systems & Process Improvement
- Provide functional support for Finance applications, resolving production issues and tracking recurring problems to a permanent fix.
- Translate Finance requirements into system solutions: business requirements, process flows, functional specifications, and test scenarios.
- Partner with the Accounting/NetSuite lead to improve NetSuite - saved searches, reports, workflows, and multi-currency and intercompany setup - so data is right at the source.
- Plan and run user acceptance testing for new features, releases, and integrations; manage defects and validate results downstream after go-live.
- Lead the finance systems and data workstream when we acquire a new brand: entity setup, data migration, and integration of its sales channels.
Controls & Access Governance
- Run access governance, periodic access reviews, and segregation-of-duties checks in support of audit and internal-control requirements.
- Maintain system and data documentation, SOPs, and training materials for finance users.
Foundation for AI & Scale
- Build the validated data foundation that our AI and agent initiatives across Finance and FP&A depend on.
- Identify automation opportunities and support the rollout of AI-enabled workflows, automated reporting, and agents that let the finance function scale without adding headcount at the same pace.
What Success Looks Like in Your First 12 Months
- First 3 months: map our end-to-end finance data flows, set up a single data-issue log with clear owners, and deliver the first core reconciliations - Seller Central to NetSuite, inventory, and cash.
- Months 3-6: those reconciliations run automatically with alerts, and the first certified data set (sales and margin) is used directly by FP&A.
- Months 6-12: the leadership KPI pack runs entirely on certified data, a standard data-integration playbook is in place for newly acquired brands, and the first AI and agent pilots in Finance and FP&A are live on the validated foundation.
What We're Looking For
Experience & Background
- 3-8 years in finance data, analytics engineering, financial systems, or e-commerce finance operations, with a focus on finance and accounting data.
- A proven track record of reconciling and validating financial data across multiple systems (ERP, marketplaces, data warehouse) - and of replacing manual checks with automated ones.
- Hands-on NetSuite experience in a finance context.
- Involvement in at least one ERP implementation, data migration, or post-acquisition integration from discovery through go-live.
- Experience in e-commerce, consumer products, retail, or another physical-product business; Amazon marketplace data experience is a strong advantage.
- Undergraduate degree in Accounting, Finance, Information Systems, Economics, Business, or a related field.
- Fluency in English; German language skills are a plus.
Accounting & Process Knowledge
- Solid understanding of core accounting processes - GL, AP, AR, intercompany, revenue recognition, inventory and COGS, and the record-to-report cycle.
- A clear view of where e-commerce data typically breaks: marketplace settlements and fees, FBA inventory, reimbursements, landed cost, and FX.
- Working knowledge of multi-entity, multi-currency accounting and how data and configuration choices affect financial reporting and audit.
Technical Skills
- Strong SQL for data extraction, transformation, validation, and reconciliation; hands-on BigQuery experience strongly preferred.
- Experience building version-controlled data and tests and setting up data-quality monitoring and alerts.
- Working knowledge of NetSuite saved searches and workflows; SuiteScript is a plus.
- Advanced Excel, and comfort using AI tools (e.g. Claude) to speed up analysis, documentation, and prototyping.
Ways of Working
- Strong analytical mindset with rigorous attention to detail, testing, and documentation.
- Ability to own ambiguous problems end to end: scope the issue, design the fix, implement or coordinate the change, and confirm the outcome.
- Clear, persuasive communicator who can explain a data problem to accountants and engineers alike - and keep pushing until the owner fixes it.
- Proactive, self-motivated, and comfortable prioritising in a fast-paced, scaling organisation.
Nice to Have
- NetSuite certification (e.g. SuiteFoundation or Administrator).
- Experience with order management or integration platforms (e.g. Pipe17, Celigo) and spend-management tools (e.g. Ramp).
- Experience with BI tools such as Tableau or Looker, or with Python for data work.
- Prior work in a buy-and-build, roll-up, or multi-brand environment where new entities are integrated frequently.
- Exposure to AI or agent use cases in finance.
unybrands is an equal opportunity employer and considers all applicants for employment without any regard to race, skin color, religion, gender identity, sexual orientation, and age. Nor are applicants discriminated against based on disability or protected classes.
