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Salary
$64k – $137k per year (Estimated)
Location
Remote/Hybrid (Budapest, Hungary)
Seniority
Architect · 7+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Founded in 2023, Zocks is an AI-powered platform designed specifically for financial advisors to streamline client interactions and administrative tasks. The software acts as an intelligent assistant, automatically joining virtual meetings or capturing notes during in-person sessions to generate structured summaries, compliance documentation, and follow-up emails. By integrating directly with existing CRM platforms and financial tools, the company enables wealth management professionals to reduce operational overhead and focus more on client relationships.

Why we're hiring for this role

Data is becoming a strategic capability at Zocks, and we're looking for an experienced Head of Data /Data Manager to help shape what comes next.

You'll join at an exciting stage, leading our small team of Data Analysts while building out the function with Data Scientists and Data Engineers. This is a unique opportunity to define how the team operates, hire exceptional talent, establish scalable processes, and partner closely with Product and Engineering to maximize the impact of data across the company.

At Zocks, Data is a core product capability-not a standalone reporting function. Your work will help shape product decisions, improve customer outcomes, and support the continued evolution of our AI-native platform.

Job Description

As Head of Data at Zocks, you will lead the Data team and ensure it delivers meaningful impact across Product, Engineering, and the business.

This isn't a role where you'll inherit a large, mature department. Instead, you'll have the opportunity to shape how Data operates at Zocks-helping define the team structure, hiring key talent, establishing scalable processes, and partnering closely with Engineering and Product to build a data function that grows with the company.

You'll be responsible for growing the team, setting priorities, improving delivery, and helping establish scalable ways of working as our data organization expands. While you'll bring enough technical depth to collaborate effectively with Data Analysts, Data Engineers, and Engineering leaders, your primary focus will be people leadership, building scalable processes, cross-functional collaboration, stakeholder management, and turning data into business and product value.

What You'll Own

Build and grow the Data organization

  • 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.

Drive Data strategy and execution

  • 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.

Partner across the company

  • 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.

Champion data quality and governance

  • 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.

Required Skills and Qualifications

  • 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.

Preferred Qualifications

  • 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.
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