Data Engineering Manager
vor 4 Wochen
Locations: Vienna, Paris, Munich, London | Hybrid
Do you want to be part of one of the fastest-growing AI companies in Supply Chain Risk Management?
At Prewave, we are dedicated to unlocking an unprecedented level of efficiency, transparency and resilience in the supply chain for our customers. We pioneer supply chain risk management with our AI-powered solutions, analysing traditional and social media in 400+ languages and predicting risks and disruptions all over the world. We help our clients to achieve a sustainable supply chain and to prevent disruptions.
We are already a trusted partner of AbInBev, BMW, Kärcher, PwC, Porsche and many more. With the increasing importance and attention to supply chain due diligence in Europe, we grow every day, and so does our team
We are looking for somebody to join us on this exciting journey to lead our efforts around business data and business intelligence.
The Go-To-Market Data Engineering Manager will ensure we organise internal and external data so that we can understand business performance and trends and steer our business in a data-driven manner.
Your missionAs our Data Engineering Manager at Prewave, you will…- Build data infrastructure combining key data sources (CRM, headcount data, finance data, external data, etc.), ensuring we capture historical data and create a clean database.
- Create a reporting layer on top of the data lake that allows for both centrally created reporting as well as user self-serve dashboard creation and data analysis.
- Construct out central dashboarding to run and monitor the business.
- Roll out reporting tool as well as individual dashboards to the Go To Market organisation in collaboration with the Sales Excellence and Enablement function and drive adoption.
- Provide strategic insights to business leadership derived from internal and external data, e.g. sweet spots where we are especially successful in winning fast and often, pipeline health, and sales rep performance.
- Bachelor's degree in STEM or economics.
- 7+ years of role-specific work experience working in analytics, data, business intelligence, etc.
- Proven track record in building data infrastructure “from scratch”.
- Experience with analysis and reporting software (Tableau etc.).
- Ability to work with large amounts of data and clean and analyse it at scale.
- Ability to distill crisp, tangible insights from large amounts of data and to derive business insights and actions from it.
- Experience designing and building user-friendly, insightful and actionable dashboards (e.g. in Tableau or similar software, directly in CRM).
- Knowledge of some machine learning/AI methodologies to enrich and improve data.
- Experience working in a B2B SaaS Software company.
- Experience working with sales and other Go-To-Market teams (e.g. business development, partner, customer success, marketing).
- An extensive compensation package
According to our collective agreement, the minimum salary for this role is EUR 3,724 gross per month, however the higher packages are likely based on your qualifications and experience. - A dynamic team in an open and inclusive work atmosphere
As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re dedicated to building teams with a wide variety of backgrounds, identities, and experiences. - Various opportunities to develop your career within the company
We are committed to building our team spirit based on mutual respect and support. We help each other achieve personal and shared goals. - Opportunity to be part of a highly innovative Austrian tech startup
We blaze the trail in our field, and we strive to help large firms ensure ethical and sustainable practices throughout their entire supply-chain processes. - A family-friendly environment
We offer flexible working hours and home-office possibilities to support a healthy work-life balance.
Prewave is an AI startup building a global supply chain intelligence platform. It's our mission to make supply chains more transparent, resilient & sustainable.
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