I build the automation that takes enterprise data from raw ERP extraction to decision-ready insight — and I read it with a business education behind me, so the output is a recommendation, not just a dataset.
I lead the Zurich cluster for Data & Intelligence Delivery at EY, coaching a team of five and owning the data pipeline that audit and advisory engagements run on — ERP extraction, transformation, analytics, and the governance that keeps all of it defensible.
What pulls me in is automation. Every engagement starts with a manual process someone has accepted as unavoidable, and most of them aren't. I've spent four years replacing those with scripted extractions, Alteryx workflows and Python routines that turn weeks of coordination into something repeatable.
That second half comes from my economics and international business background. I studied real estate and investment in Cracow, took an MSc in International Business at ZHAW, and spent a detour in law and psychology before that. It means when a client asks what a finding implies for their close process or their risk exposure, I can answer in their language rather than handing over a dashboard.
The combination is deliberate. Plenty of people can write the query; plenty can run the client conversation. I'm most useful in engagements that need both at once — complex extraction with a stakeholder who needs to understand what just happened, often in German, often under audit deadline.
Selected delivery work across Swiss listed and multinational groups — the kind of engagement where the ERP is unusual, the timeline is fixed, and the client needs a person who can do both the extraction and the conversation.
Building the pipeline from client ERP to analysis-ready data — and automating away the manual steps that usually sit in the middle.
Turning the extracted data into something an audit team or a client executive can act on directly.
The part that makes the technical work land — coordinating the people on both sides of the engagement.
Leading a five-person cluster across analytics delivery for Swiss audit and advisory engagements. Designing ETL pipelines and automations, owning data governance, building Power BI dashboards, and advising clients directly on what the findings mean for their business.
Processing large, complex financial datasets with SQL, Python and Azure Databricks. Statistical analysis, database maintenance, and visualisation for audit stakeholders across multiple concurrent engagements.
A short self-assessment I put together and have kept current — personality, what motivates me, and the environment where I do my best work.
I'm well suited to a changing, fast-paced team where there are no ambiguities of leadership and I'm accountable for the results I produce.
I need to work with others — I thrive on the buzz and am likely to become bored working alone. I'm often adept at fast-paced environments where I can act on opportunities as they arise.
What slows me down: no factual, goal-oriented approach; unclear deadlines; lack of resources to reach the goal; and a tech stack that won't allow the automation the problem actually needs.
Ikigai (pronounced ik-i-gai) is a Japanese concept meaning "a reason for being."
Activities that allow one to feel ikigai are never forced on an individual; they are often spontaneous, and always undertaken willingly — giving the individual satisfaction and a sense of meaning in life.
It sits at the intersection of four questions: what you love, what the world needs, what you're good at, and what you can be paid for.
I first mapped this while finishing my Master's, when the answer pointed towards investment advisory. Four years of building data pipelines later, the shape has stayed the same but the content has moved: the same instincts — systems thinking, creativity, wanting to teach — now point squarely at automation and analytics.
What changed isn't what drives me. It's that I found the version of it where the business education and the technical work reinforce each other instead of competing.
Peer-nominated recognition from senior colleagues and engagement leads across four separate nominations — for delivery, for teaming, and for the things that don't show up in a workplan.
"Thank you for going the extra mile with the Geberit Cube!"
"Your hard work, professionalism and positive energy have had a meaningful impact on the team. Thank you for everything you do."
"Little appreciation for your great teaming and for your enthusiastic efforts. Keep rocking!"
"Thank you for organizing the Zurich lake cruise with apéro and dinner. Such a nice change from the usual dinner!"
During her tenure with us, Zuzanna has consistently demonstrated qualities that make her a loyal team member. She is punctual and kind and has a track record of not only meeting but also surpassing the expectations set for her projects. Moreover, Zuzanna is a person of integrity and reliability, regularly meeting deadlines without fail. Her interactions with colleagues are marked by politeness and respect, fostering a positive work environment.
"Completed all assigned tasks to our fullest satisfaction. Noted for exemplary conduct, loyalty, sense of responsibility and willingness to help."
"Strong work ethic and flexibility, consistently willing to take on additional responsibility — kept a clear head and worked efficiently even in difficult situations."
"Always punctual, hardworking and reliable. Worked cleanly and conscientiously, completed assigned tasks to our full satisfaction."
"Settled into the role in remarkably little time. Friendly, quick, diligent and precise — discreet and entirely trustworthy."
University-issued programmes and technical certifications. Click any card to open the course.
Verified originals held on file — scanned copies provided on request.
Open to conversations about data, automation and audit technology — especially where the technical problem and the business problem are the same problem. Scan to open this page.
