Analytics Engineering Manager - RevOps
Mollie
Build with us
Since 2004, we’ve had one clear goal: to make payments and money management effortless for every business in Europe. Today, more than 250,000 companies use Mollie to get paid, manage money and grow – with products designed to be simple, scalable, and dependable. With 950+ Mollies across 14+ locations, we care deeply about autonomy and craft. So we work in small teams, with real ownership, and we trust you to make the right decisions. We’re building for the long term, so we provide the tools you need, processes you can rely on, and a balanced work environment to help you do work you’re proud of. Sound like your kind of place? Let’s build together. Your impact Analytics Engineering at Mollie is a craft we take seriously. As Analytics Engineering Manager for RevOps, you sit at the intersection of people leadership and technical craft, responsible for both the growth of the Analytics Engineers you manage and the quality of the work they produce. You will lead a team of approximately six direct reports, spanning the RevOps domain and analysts in adjacent domains such Planning & Analysis and Mollie Connect, making sure the craft is well represented and well applied across all of them. The RevOps domain is central to how Mollie understands and demonstrates its commercial performance. You will own the domain metrics together with your team, ensuring that what gets measured actually gets used, and that stakeholders across the business can see the impact of the work being done. Beyond the domain itself, you will help shape how Analytics Engineering as a craft evolves at Mollie, setting standards, improving ways of working, and making sure the teams you support know how to get the most out of the craft. This is a role for someone who is equally comfortable coaching a direct report through a tricky career conversation and reviewing a dbt model for quality. You will partner closely with accountable leads on planning and roadmaps, advocate for the craft with non-technical stakeholders, and drive initiatives that raise the bar across the whole Analytics Engineering community at Mollie. What You’ll Ship- A consistent, high-quality Analytics Engineering practice across the RevOps domain and supported adjacent teams, with clear standards, documented ways of working, and a team that applies them reliably
- A well-maintained and trusted set of RevOps domain metrics that give stakeholders a clear, consistent view of business performance and commercial impact
- A structured performance management cycle for your direct reports, including regular feedback, meaningful reviews, and development goals that are set and tracked in genuine partnership with accountable leads
- Craft-level initiatives that improve how Analytics Engineers work across teams, from tooling and best practices to knowledge sharing and onboarding
- A planning and prioritisation process that supports accountable leads effectively, with Analytics Engineering work scoped, sequenced, and delivered to a high standard
- A team of Analytics Engineers who are growing in their craft, supported through coaching, mentoring, and learning opportunities that are tailored to where each person wants to go
- At least five years of experience in an analytics or analytics engineering environment, with a background in a quantitative discipline such as mathematics, engineering, econometrics, or a related field
- Experience leading or managing analytics engineers or analysts, with a track record of supporting people through feedback, development conversations, and performance cycles, and a genuine interest in helping others grow
- The ability to partner effectively with commercial teams such as sales, marketing, and revenue operations, translating between what the business needs and what the craft can deliver
- Solid hands-on experience with SQL and a cloud data warehouse, with the ability to review and contribute to technical work directly
- Practical experience with dbt or an equivalent data modelling tool, and a clear understanding of what good data modelling looks like in practice
- Familiarity with a BI tool that includes a semantic layer, such as Looker or similar, and an understanding of how these tools connect to downstream business use cases
Offerta di lavoro pubblicata un mese fa
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