People Analytics Data Engineer: Build HR Data Infra

Bee Talent Solutions; San Jose (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Bee Talent Solutions is seeking a data engineer at the intersection of data engineering and People analytics to build the technical foundation powering insights about the employee lifecycle, from hiring to exit, while experimenting with AI to improve data infrastructure efficiency.

As a member of the people analytics team, you will design scalable data architectures, optimize our analytics stack, and transform raw data into trusted, reusable datasets for self-serve analytics.

Qualifications

• 3+ years in data or analytics engineering with experience in people analytics.
• Expert in Snowflake or other cloud tools, with optimization and performance tuning.
• Proficient in SQL and Python; familiar with dbt.
• Experience with visual analytics tools (Tableau, Looker).
• Experience implementing data security and privacy controls in cloud environments.
• Comfortable with messy or incomplete data.
• Creative and scrappy, results-oriented with a bias toward flexibility and impact.

Responsibilities

• Create a scalable data foundation that supports visualization tools such as Tableau or HR analytics tools such as Visier platform, and enables strategic insights across the company.
• Design scalable data architectures and build dimensional models that transform raw data into trusted, reusable datasets for self-serve analytics while maintaining performance
• Model downstream tables for custom reporting and analytics
• Partner with IT to implement data governance including documentation, lineage tracking, quality monitoring, and proactive alerting systems
• Develop and maintain automated reporting solutions that scale with organizational growth

Skills

Data engineering

People analytics experience

SQL

Python

Data visualization

Tools

Snowflake

dbt

Tableau

Looker

Job description

Bee Talent Solutions is seeking a data engineer at the intersection of data engineering and People analytics to build the technical foundation powering insights about the employee lifecycle, from hiring to exit, while experimenting with AI to improve data infrastructure efficiency.

As a member of the people analytics team, you will design scalable data architectures, optimize our analytics stack, and transform raw data into trusted, reusable datasets for self-serve analytics.