Data Engineer (Finance)

TL;DR

Data Engineer (Databricks/SQL): Building and maintaining a high-quality, SOX-compliant Finance data ecosystem to enable analytics and AI-driven decision-making with an accent on semantic model development and data governance. Focus on engineering scalable Delta tables, ensuring data accuracy through automated reconciliations, and optimizing ingestion pipelines.

Location: Hybrid (Warsaw, Poland)

Company

hirify.global is a global beauty company focused on creating an inclusive workplace and driving digital transformation within its Finance and IT operations.

What you will do

• Develop and operate a robust Finance data quality framework, including validation, anomaly detection, and monitoring controls.
• Design and maintain scalable semantic models and curated Finance layers using Databricks and Power BI.
• Perform automated data reconciliation between the Data Cloud and ERP systems to ensure SOX 302 & 404 compliance.
• Build and optimize performant ingestion pipelines following engineering best practices.
• Collaborate with FP&A and IT stakeholders to translate financial reporting requirements into technical data solutions.

Requirements

• Bachelor’s or Master’s degree in Data Engineering, Computer Science, Finance, or a related field.
• Strong hands-on experience with Databricks, SQL, Delta Lake, and Lakehouse architecture.
• Proficiency in Power BI semantic models, including DAX and tabular modeling.
• Solid understanding of Finance processes (GL, FP&A, budgets) and SOX audit requirements.
• Experience with data quality frameworks and lineage documentation.
• Location: Must be based in or able to work hybrid in Warsaw, Poland.

Nice to have

• Experience with enterprise-scale Data & AI platforms.
• Exposure to MDM, data cataloging, and governance tooling.
• Knowledge of ERP systems such as SAP or Oracle.
• Python skills for automation and testing.

Culture & Benefits

• Opportunity to shape the Finance data foundation and create a single source of truth.
• High visibility and collaboration with global Finance and IT stakeholders.
• Exposure to modern data, analytics, and AI technologies.
• Hybrid working model with flexible ways of working.
• International, transformation-driven corporate environment.