Data Engineer for QA Metrics & Dashboards

Kforce Inc; San Mateo (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Kforce is seeking a Data Engineer to support PSQA efforts in Foster City, CA. You will design dashboards, build ETL pipelines, and model release- and version-based data to enable longitudinal analysis and quality tracking.

You will work with SQL, Python (Pandas/PySpark), and BI tools (QuickSight/Tableau/Power BI) while collaborating with cross-functional stakeholders to translate quality needs into actionable insights.

Qualifications

• Strong SQL skills for querying, aggregation, and data modeling.
• Python proficiency (Pandas/PySpark) for ETL.
• Experience building dashboards with BI tools (QuickSight, Tableau, or Power BI).
• Ability to model release/version-based data for longitudinal tracking.
• Basic data science skills - statistics, EDA.
• Familiarity with AWS fundamentals (S3, Athena/Redshift).
• Experience with Git for version control.
• Strong written and verbal communication skills.

Responsibilities

• Design, build, and maintain dashboards and scorecards for PSQA release and quality metrics.
• Query, aggregate, and transform release/version data using SQL and Python.
• Develop ETL pipelines to process and simplify quality and release data from multiple components.
• Model release- and version-based data to enable tracking and trend analysis over time.
• Perform exploratory data analysis to surface insights and support data-driven quality decisions.
• Collaborate with PSQA and cross-functional stakeholders to translate quality and release needs into actionable dashboards.
• Take ownership of assigned data deliverables, driving issues to resolution independently.
• Document data models, pipeline logic, and dashboard definitions for maintainability.

Skills

SQL

Python

BI tools

Data modeling

Data analysis

Communication

Tools

Git

Airflow

PySpark

Pandas

S3

Redshift

Athena

Job description

Kforce is seeking a Data Engineer to support PSQA efforts in Foster City, CA. You will design dashboards, build ETL pipelines, and model release- and version-based data to enable longitudinal analysis and quality tracking.

You will work with SQL, Python (Pandas/PySpark), and BI tools (QuickSight/Tableau/Power BI) while collaborating with cross-functional stakeholders to translate quality needs into actionable insights.