Data Engineer working with People Analytics to structure and evolve data ecosystems in a fashion company. Ensuring reliable and scalable data for strategic decision-making.
Responsibilities
Develop, maintain, and optimize robust data pipelines to support analyses, products, and predictive People Analytics models at scale;
Integrate data from multiple HR & People systems (ATS, payroll, LMS, performance reviews, engagement surveys, etc.), ensuring quality, consistency, and governance;
Build, structure, and evolve data models (Data Lake/Data Warehouse) focused on the employee journey and executive needs;
Perform data ingestion, transformation, and modeling using cloud services (AWS, GCP, or Azure), focusing on efficiency and scalability;
Implement and maintain best practices for versioning, documentation, security, and data quality;
Conduct data quality assessments, proposing and implementing structural and process improvements;
Collaborate with BI Analysts and HR/People teams to translate analytical needs into scalable engineering solutions;
Automate routines and workflows to ensure reliability, stability, and continuous updates of data sources;
Monitor and improve ETL/ELT processes, ensuring performance and reducing rework;
Support strategic initiatives — such as AI models — by providing structured, accessible, and reliable data.
Requirements
Bachelor's degree: Engineering, Information Systems, Computer Science, Systems Analysis, Statistics, or related fields;
Experience programming in data-oriented languages (e.g., Python, R, Scala, etc.);
Experience with software engineering best practices (e.g., documentation, version control, automated testing, clean code, etc.);
Experience with data architecture and modeling in Data Lakes, preferably on GCP;
Experience implementing, maintaining, and orchestrating data pipelines (Airflow);
Knowledge of relational databases, such as MySQL, SQL Server, PostgreSQL, etc.;
Knowledge of ETL processes and tools;
A continuous learning mindset and willingness to develop new techniques and tool skills;
Ability to solve complex problems using logical reasoning;
Strong communication skills and ability to work in a team;
Eagerness to learn and acquire new skills on a day-to-day basis.
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