AI & Automation Engineer Finance (m/w/d)

Our DNA

We are an innovative digital voucher platform that collaborates with over 500 top brands such as Amazon, Google, Apple, IKEA, Zalando, and many more. As a leading multi-brand voucher provider, Wunschgutschein has disrupted and conquered the market over the past few years! Operating under the Wunschgutschein brand in Germany and Wishcard in other European countries, we are active at more than 120,000 brick-and-mortar points of sale and are currently a household name for more than a third of Germans. To date, Wunschgutschein has sold over 100 million vouchers and, as the undisputed No. 1 gift voucher provider, continues on its growth trajectory. The Wunschgutschein voucher is the perfect gift for everyone, from private occasions to employee retention and motivation, as well as customer loyalty and acquisition.

To strengthen our finance department, we are looking for someone who will strategically and operationally drive the use of artificial intelligence and automation. The focus is on developing new solutions, not maintaining existing reports.

The foundation for this has been laid: SSAS cubes for sales, redemptions, and purchases; established Power BI dashboards; an internally managed data warehouse; and largely automated reporting processes. Building on this, we are pursuing two independent initiatives:

• Automated anomaly detection: A set of rules that systematically identifies anomalies in daily data, instead of requiring manual searching.
• AI-supported month-end closing: Intelligent analysis and auditing processes that relieve controlling departments of recurring routine work.

This position is newly created and reports directly to the Head of Finance. You will not only be responsible for implementation, but will also play a key role in shaping which processes are automated and how.

Your playing field

Your goal: To consistently transform manual testing and preparation work into rules, models and agents, thereby creating space for tasks that require professional judgment.

• You will integrate AI and agents into regular operations. You will bring agent-based analytics into productive use and strategically deploy Large Language Models where they create real added value. Where deterministic logic is the better choice, you will consistently implement it. You will have a say in decisions regarding the technology stack and budget.
• Streamline the month-end closing process. As a key focus, you will work with the controlling department to develop an AI-supported model that automates recurring audit and analysis steps, from reconciliations and plausibility checks to completeness checks and variance analyses. Based on historical financial statements, the model learns what is within the normal range and what requires explanation.
• Establish automated data monitoring. You will design and implement a rule set that checks parameterized daily data across all channels and data sources. You will calibrate the thresholds in close coordination with business partners.
• Empower the team. You design automation solutions so that business partners can use them independently. The goal is a team that uncovers anomalies and critically examines them, rather than simply processing reports.
• Evaluate findings and initiate appropriate measures. You not only identify anomalies but also classify them professionally: What are the causes, how relevant is the finding, and what action is required? You share your findings with the segment managers and discuss with controlling and management whether and how countermeasures need to be taken.

That's what makes you who you are

• More than three years of professional experience in Analytics Engineering, Data Engineering or Business Intelligence with a clear focus on automation and AI applications rather than reporting.
• Demonstrable implementation success. You have brought at least one automation solution into production that runs reliably and independently of you, including error handling, monitoring, versioning, and documentation. This practical evidence is more important to us than any certification.
• Solid technical knowledge: confident handling of Python and SQL as well as practical experience with SSAS or multidimensional data models and Power BI.
• Practical experience with LLMs and AI agents in business processes, combined with a sound judgment about where their use makes sense and where it does not.
• Strong business acumen and high level of initiative. You want to understand why a key performance indicator (KPI) changes before defining a rule for it. You independently evaluate findings and proactively identify automation potential instead of waiting for requirements.
• Strong communication skills and a passion for sharing knowledge. You prepare observations in a way that enables segment managers to make informed decisions, and you clearly indicate when a figure is not yet reliable. You empower colleagues to use the tools independently. Fluency in German and English completes your profile.

Desirable

• Experience in retail, e-commerce or the voucher business.
• Knowledge of financial processes, especially month-end closing and reporting.
• Experience in processing large amounts of data, regardless of the framework used.

What we have in store for you

• A reliable data foundation: Our cubes and dashboards run stably and are managed internally; you don't start with cleanup work, but directly with further development.
• Dedicated budget: For infrastructure, LLM usage and monitoring tools.
• Scope for creativity and short decision-making processes: Direct reporting line to the Finance management and close cooperation with Controlling, Treasury and the segment managers.
• Flexibility through the option to work from home one day per week.
• Additional benefits: €50 tax-free allowance per month (after successful completion of the probationary period) & an attractive meal allowance for your office days.

We look forward to receiving your CV and a brief description of an automation solution you have built that is still in productive use today, including what went wrong along the way.

Work location: On-site