People Data Analyst

Overview:

The People Data Analyst supports the HR function by transforming complex workforce data into actionable insights. This role is responsible for analyzing HR datasets, building dashboards, managing data pipelines, and maintaining server infrastructure. Working closely with HR and People Operations teams, the analyst ensures data accuracy, streamlines reporting processes, and helps drive evidence-based decisions on talent, engagement, and performance.

Responsibilities:

Data Analysis & Reporting:

• Perform exploratory data analysis (EDA) on HR datasets (turnover, recruitment, performance, engagement).
• Design, build, and maintain dashboards and regular reports for HR business partners and senior leadership.

Database Management:

• Write and optimize SQL queries against relational databases (e.g. PostgreSQL, MySQL).
• Ensure data integrity, define tables, indexes, views, and stored procedures as needed.

Data Engineering:

• Develop and manage ETL processes to ingest and transform HR data from multiple sources (ATS, LMS, payroll systems).
• Automate data workflows using tools such as Apache Airflow, dbt, or similar.

Server & Infrastructure:

• Deploy and maintain data services on Linux-based servers or cloud instances (AWS EC2, Azure VM).
• Monitor server health, performance, security patches, and backups for data environments.

Collaboration & Stakeholder Management:

• Partner with HR Business Partners and People Operations teams to define metrics and analytics requirements.
• Present findings and recommendations in clear, non-technical language.

Continuous Improvement:

• Identify opportunities to streamline data processes, improve data quality, and introduce new analytics tools or methodologies.

Qualifications:

Databases & SQL:

• Strong command of SQL for data extraction, joins, window functions, and performance tuning.
• Experience with at least one RDBMS (PostgreSQL, MySQL, or SQL Server).

Data Engineering & ETL:

• Hands-on experience building ETL pipelines; familiarity with Apache Airflow, dbt, Talend, or similar.
• Ability to write clean, modular Python scripts for data transformation.

Server Administration:

• Comfortable working on Linux servers: SSH, basic shell scripting, package management.
• Experience provisioning and managing cloud instances (AWS EC2, Azure VM, or GCP Compute Engine).

Analytics & Visualization:

• Proficiency in Python (pandas, NumPy) or R for data analysis.
• Skilled in dashboard tools such as Tableau, Power BI, or Looker.