Senior Analytics Engineer

sailpoint; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

SailPoint is seeking an Analytics Engineer to join our IT Data Engineering team. You will design and maintain data models and pipelines in BigQuery, focusing on HR and People Analytics to provide trusted reporting and analytics across the company.

You will own data from ingestion to the reporting layer, write SQL, tests and docs, implement access controls, and build Tableau dashboards for HR and leadership. Collaboration with stakeholders and adherence to CI/CD practices are essential.

Qualifications

• 5–8 years of analytics/data engineering experience.
• Advanced SQL skills with window functions and tuning.
• Hands-on dbt experience with tests and docs.
• Experience with BigQuery or cloud data warehouse.
• Experience with data pipelines and orchestration tools like Airflow.

Responsibilities

• Design and maintain modular dbt models in BigQuery to produce clean datasets.
• Write performant SQL and optimize queries for speed and cost.
• Build data ingestion pipelines from source systems and SaaS apps like Workday.
• Develop orchestration for data workflows and monitor data arrivals.
• Define standardized business metrics (headcount, attrition, recruiting).
• Ensure data privacy and access controls, including Row-Level Security.
• Create Tableau data sources and dashboards for HR and leadership.
• Participate in CI/CD, version control, and deployment practices.

Skills

Advanced SQL

dbt

BigQuery

Airflow

Tableau

Git

Data modeling

Data privacy

Education

Bachelor's degree in STEM or related field

Tools

Fivetran

Airbyte

Cloud Composer

Python

Job description

The Role

SailPoint is the leader in identity security for the cloud enterprise. Our solutions help thousands of organizations worldwide see and govern who has access to what, so every identity has exactly the access it needs.

SailPoint is seeking an Analytics Engineer to join our IT Data Engineering team. In this role, 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.

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.
• Support Tableau administration for the content you own, including user permissions, publishing workflows, and refresh schedules.
• Build datasets that support workforce analytics and forecasting use cases, such as attrition and recruiting capacity planning.
• Explore and help implement AI-assisted analytics, such as self-service query tools built on BigQuery and Google Gemini, for HR and other business partners.
• Troubleshoot data issues end to end, from source system through transformation to reporting, and drive root-cause fixes.
• Contribute to CI/CD, version control, and deployment practices for the team's data projects.
• Partner with business stakeholders to gather requirements, define KPIs, and scope new data products and visualizations.
• Contribute to data modeling standards, naming conventions, and reusable patterns for the broader data team.

Requirements

• 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.

Preferred

• Bachelor's degree in a STEM, business, or related field, or equivalent experience.
• Experience with HR or workforce data, such as headcount, attrition, and recruiting funnel reporting.
• Experience with Workday data, including custom reports or integrations that feed downstream analytics.
• Experience using AI tools for analytical querying or building AI-assisted self-service reporting.
• Experience with Python for data pipelines, automation, or analysis.
• Experience with data ingestion tools such as Fivetran, Airbyte, or similar.
• Familiarity with Google Cloud Platform services beyond BigQuery.
• Experience in a SaaS or cybersecurity environment.

Plan for Success

Days 1-30: Integration & Core Tech Onboarding

Focus on gaining environment access, mapping pipeline architectures, and aligning with key stakeholders.

Tech Stack Setup

Set up your developer environment and establish full access to Google BigQuery, dbt, Git, and Tableau.

Architecture Mapping

Conduct a deep dive into active dbt models