Hybrid Data Engineer, People Analytics

Posted last month

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About the role

  • 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.
  • Differentials:
  • Experience with BigQuery or Kubernetes

Benefits

  • Health allowance
  • Wellness program
  • Professional development opportunities
  • Hybrid work

Job title

Data Engineer, People Analytics

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

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