Hungary
EuropeHead of Data
1 мес. назад
HungaryEuropeHeadHybrid
data analysisdata infrastructureai
Experienced leader to build and lead a high-performing data organization for better product decisions and scalable data infrastructure at an AI startup.
О компании
- Company Overview: We're , a venture capital-backed AI startup changing the world of financial services, and other industries that value security and privacy. Our founding team built their careers working on real-time communication products, building enterprise platforms, and crafting tools for some of the most security-conscious industries. With experience gained from industry leaders like Twilio, IBM, Microsoft, and Hearsay Systems, we're using AI to bridge human conversations with enterprise systems, starting with financial services. Our focus, although simple, is powerful: reinventing business operations and transforming the areas that often get bogged down by slow, inefficient processes. Our innovative platform allows people to communicate naturally, while we capture the inf
- Work closely with Product Managers to identify opportunities where data creates measurable customer value.
- Partner with Engineering to build scalable, reliable data infrastructure and analytics capabilities.
- Collaborate with business teams to deliver actionable insights that support strategic decision-making.
- Communicate technical concepts clearly to both technical and non-technical stakeholders.
- Act as the bridge between business needs, product strategy, and technical implementation.
Требования
- 7+ years of experience in Data, Analytics, Business Intelligence, or related disciplines.
- 2+ years of experience in leading Data teams within a B2B SaaS product company.
- Experience managing or working closely with both Data Analysts and Data Engineers.
- Proven track record of hiring, mentoring, and developing high-performing technical teams.
- Strong understanding of analytics, data modeling, ETL processes, data warehousing, and modern data architectures.
- Solid understanding of concepts such as data dictionaries, semantic layers, data governance, and scalable analytics foundations.
- Ability to discuss technical topics with engineers while translating business needs into clear priorities.
- Experience working closely with Product Management and Engineering organizations.
- Strong stakeholder management, prioritization, and delivery leadership skills.
- Experience leading cross-functional initiatives in fast-paced environments.
- Excellent English communication skills; fluent Hungarian is also required.
Будет плюсом
- Experience scaling a Data organization from a small team into a larger function.
- Experience working with US-based customers, stakeholders, or product organizations.
- Experience with AI-powered or data-intensive products.
- Familiarity with cloud platforms such as AWS.
- Working knowledge of SQL and Python sufficient to understand technical trade-offs and support technical decision-making.
- Experience with modern BI and analytics platforms.
- Experience establishing data governance practices, metric definitions, or data dictionaries.
- Exposure to Data Science or Machine Learning teams.
Другое
- Lead, mentor, and coach a growing team of Data Analysts while expanding the organization with Data Scientists and Data Engineers.
- Define team responsibilities, ownership areas, and effective ways of working.
- Recruit exceptional talent and help shape the future structure of the Data organization.
- Foster a collaborative, high-performing culture built on ownership, continuous learning, and business impact.
- Support career development through coaching, regular feedback, and clear growth paths.
- Define priorities together with Product and Engineering leadership.
- Help shape how data powers our AI-native product, enabling better customer experiences, smarter product capabilities, and stronger business decisions.
- Balance short-term business needs with long-term investments in data quality, infrastructure, and scalability.
- Drive successful delivery of analytics initiatives across multiple teams and stakeholders.
- Continuously improve planning, execution, and operational processes within the Data organization.
- Promote best practices around data governance, documentation, and data quality.
- Drive consistency in metrics definitions, business logic, and data models across the organization.
- Establish scalable standards for data cataloging, documentation, and data dictionaries.
- Ensure the team delivers trusted, high-quality data that enables confident decision-making.