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About Us
HiBob helps modern, mid-size businesses transform the way they manage people, giving HR and managers all they need to connect, engage, develop, and retain top talent. Since 2015, we’ve achieved consecutive triple-digit year-over-year growth, all backed by our amazing team of Bobbers from across the globe, making us the choice HRIS of over ~4500 midsize and multinational companies and over 1 Milion users.
Our HR platform is intuitive, data-driven, and built for the way people work today: globally, remotely, and collaboratively.
About the role:
As a Data Solution Architect , you will play a key role in ensuring that data is accurate, structured, and optimized for analysis and decision-making. You will collaborate closely with the business teams, data architects, and business analysts to design, enhance, and maintain data solutions.
This role suits someone with strong analytical thinking, a passion for data, and a good understanding of business logics.
Experience: 5+ years of experience in data architecture, data engineering, or a related role, preferably in large-scale, complex environments- Must
Education: Degree in Industrial Engineering & Management, Data Analytics, Information Systems, Economics, or a related field
Technical Skills:
Hands-on experience with data modeling techniques, relational and non-relational databases (SQL, NoSQL), data warehousing solutions, and ETL processes.
Experience with BI tools such as Tableau, Power BI, or Looker (development experience is an advantage but not required).
Familiarity with financial data structures (GL, P&L, budgets, forecasts, etc.).
Understanding of cloud-based data warehouses (e.g., Snowflake, BigQuery, Redshift) is a plus.
Soft Skills:
Strong analytical and problem-solving mindset.
Ability to connect data insights with business context.
Clear communication skills and the ability to collaborate across technical and business teams.
Preferred Qualifications:
Knowledge of data governance and data quality frameworks.
Familiarity with data transformation tools (e.g., DBT, Airflow, Fivetran).
Experience in a SaaS or fast-growing tech company environment.
Data Architecture & Modeling: Design and maintain scalable data architectures, ensuring efficient data flow, storage, and retrieval. Develop logical and physical data models aligned with business objectives.
AI, Agents & Advanced Data Products: Preparing data (structured + unstructured) for AI consumption, building semantic structures that allow AI agents to interpret business logic, metrics, and relationships. Designing AI-ready data products.
Business Collaboration: Work closely with business leaders and analysts to understand data requirements, ensuring alignment between data models and business needs.
Governance & Best Practices: Define and enforce best practices for data governance, security, and compliance, ensuring adherence to industry standards.
Technology & Innovation: Evaluate and recommend data technologies, tools, and frameworks to enhance our data ecosystem.
Scalability & Performance: Optimize data infrastructure for performance, scalability, and cost-effectiveness.
Integration & ETL Design: Design data pipelines and integration strategies to unify data from multiple sources.
Documentation & Standards: Establish and maintain clear documentation for data models, definitions, and data governance policies.