Senior HR Analytics Engineer — Data & Dashboards

SailPoint; Austin (TX); On-site; USD 109,000 - 183,000; Full time

Benefits offered by this job

Health and wellness coverage

401(k) Savings with company match

Flexible vacation policy

8 paid holidays

Job summary

SailPoint is seeking an Analytics Engineer to join our IT Data Engineering team in Austin. You will build and maintain the data models and pipelines that serve as the trusted foundation for reporting and analytics across SailPoint, with a particular focus on supporting our HR and People Analytics partners.

You'll own data from ingestion through the reporting layer, writing the SQL, tests, documentation, and access controls that keep it accurate, secure, and easy for others to build on.

Qualifications

• 5–8 years of experience in analytics engineering, data engineering, or a similar role.
• Advanced SQL skills, including window functions, CTEs, and query performance tuning.
• Hands-on experience building and maintaining data models in dbt, including tests, macros, and documentation.
• Experience working in a cloud data warehouse, preferably BigQuery.
• Experience building or supporting data pipelines and working with orchestration tools such as Airflow, Cloud Composer, or similar.
• Hands-on experience with Tableau Desktop and Tableau Server or Tableau Cloud, including published data sources, calculated fields, parameters, and Row-Level Security.
• Experience working with sensitive or PII data and applying data privacy and access controls.
• Proficiency with version control using Git and familiarity with CI/CD workflows.
• Strong understanding of data modeling concepts such as dimensional modeling, star schemas, granularity, and slowly changing dimensions.
• Experience gathering requirements from business users and translating them into data solutions.
• Strong attention to detail and a commitment to data accuracy.
• Clear written and verbal communication skills, with the ability to explain technical concepts to non-technical and executive audiences.

Responsibilities

• Design, build, and maintain modular dbt models in BigQuery that transform raw data into clean, reliable, analysis-ready datasets.
• Write performant, well-structured SQL, and optimize BigQuery queries and models for speed and cost.
• Build and support data ingestion pipelines that bring data from source systems and SaaS applications, including Workday, into the warehouse.
• Develop and maintain orchestration and scheduling for data workflows, and monitor pipelines to make sure data arrives on time and complete.
• Define and standardize business metrics, such as headcount, attrition, and recruiting funnel measures, so the same number shows up consistently in every report and dashboard.
• Implement dbt tests, documentation, and code review practices to ensure data quality and make models easy for others to understand and extend.
• Enforce data privacy and access controls for sensitive and PII data across models, data sources, and dashboards, including Row-Level Security.
• Build and maintain Tableau data sources and dashboards on top of your models, including operational and executive-level views used by HR and leadership.

Skills

Advanced SQL

dbt modeling

BigQuery

Data pipelines

Airflow/Cloud Composer

Tableau

Data privacy

Git & CI/CD

Dimensional modeling

Requirements gathering

Communication

Python (Preferred)

Education

Bachelor's degree in STEM or related field

Equivalent experience

Tools

dbt

BigQuery

Airflow

Tableau Desktop/Server/Cloud

Workday data

Git

Python

Fivetran / Airbyte

Job description

SailPoint is seeking an Analytics Engineer to join our IT Data Engineering team in Austin. You will build and maintain the data models and pipelines that serve as the trusted foundation for reporting and analytics across SailPoint, with a particular focus on supporting our HR and People Analytics partners.

You'll own data from ingestion through the reporting layer, writing the SQL, tests, documentation, and access controls that keep it accurate, secure, and easy for others to build on.