Data Architect

EcoVadis is embedding AI deeply into its operations and expanding its product portfolio. The Enterprise Data Architect role is critical for sustaining growth by bridging business strategy and technology strategy to evolve the Data Platform into a high-performance data mesh ecosystem treating data as a product and AI as a core competency.

• Very good knowledge of data platforms including data warehouses, data lakes, lakehouses, BI tools, and embedded analytics solutions.
• Expertise in multi-domain analytical architectures such as data mesh, medallion architecture, self-service analytics, and BI.
• Specific experience with Databricks.
• Experience with enterprise data model design, various data modeling patterns, data engineering practices, and data management standards (e.g., DAMA).
• At least 5 years focusing on architecture (data, solution, or enterprise architecture).
• Broad understanding of technical aspects of data integration including data catalogs, data quality, solution maintainability, performance, and security.
• Practical experience with MDM, RDM, CDP, ETL, ELT, rETL, SQL, noSQL, and near-real time analytics.
• Approach including people, process, and technology as a whole.
• Experience with all stages of SDLC from vision and strategy to solution design, vendor selection, technical design, workshops, implementation assistance, troubleshooting, and solution adoption.
• Good stakeholder management, verbal and written communication, and facilitation skills.
• Pragmatic approach to governance and application portfolio rationalization.
• Knowledge of data compliance frameworks (e.g., GDPR, CCPA, SOX) and ethical considerations in data usage and AI/ML model deployment.
• Team player with high self-organization.
• Ability to mentor and guide teams fostering technical excellence and innovation.
• Relevant certifications (e.g., CDMP/DAMA, TOGAF, CIPP) are a plus.
• Fluent in English.

• Build target architectures and long-term strategic roadmaps alongside Solutions, Engineering, Data, and IT teams.
• Own the Data Strategy on the architecture side, translating complex business needs into pragmatic, future-proof architectures.
• Define and govern Enterprise Data Models and Domains, expanding beyond traditional analytics to AI/ML workloads.
• Lead the architecture side of the Data Strategy, designing for AI-readiness by integrating Feature Stores, Vector Databases, and other technologies.
• Explore and validate new solutions in the data platform space based on business requirements or research.
• Perform technical Proof of Concepts, document them, and assist teams in industrializing them.
• Monitor new technological advances to help teams reduce technical debt and adopt appropriate tooling.
• Collaborate with Data Governance and AI teams to improve architecture governance practices.
• Develop and maintain policies, standards, and guidelines for consistent data platform frameworks.
• Identify discrepancies between technical architecture, agreed practices, and system designs.
• Ensure architectures adhere to data compliance frameworks (e.g., GDPR, CCPA) and ethical AI/ML deployment considerations.
• Collaborate with Product Managers and Data Product Owners to enable Data as a Product, ensuring reusability, scalability, and self-service consumption.
• Define best practices for development, maintenance, and lifecycle management of data products.
• Mentor Data Engineering and Analytics teams on data modeling patterns, best practices, and execution choices.
• Advise business and technical stakeholders on self-service data platform capabilities.
• Partner with IT team members to ensure architecture aligns with security strategy and policies.

Offer available only for candidates eligible to work and live in Poland. Location: Hybrid in Warsaw (4 days per month in the office) / Full remote from Poland.