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Elastic

Searches enterprise data and monitors systems

Analytics Engineer - HR Analytics

Data EngineeringConfirmed live in the last 24 hours
Full-timeUnited StatesNo salary listedIn-person

About the Job

Requirements

  • At least 2 years of hands-on experience building and maintaining data pipelines in Google Cloud Platform.
  • Strong SQL and Python skills.
  • Direct experience extracting and modeling data from at least one major HRIS or applicant tracking system, such as Workday or Greenhouse, through its reporting or API layer; dashboard-level reporting alone does not meet this requirement.
  • Demonstrated ability to build custom dashboards and data visualizations using standard business intelligence platforms such as Looker or Tableau, or code-based environments such as Python, Streamlit, or Plotly.
  • Broad understanding of HR programs and metrics across the employee lifecycle, including recruiting.
  • Experience working across geographies and time zones and tailoring insights to diverse audiences.

Responsibilities

  • Build and maintain data pipelines in BigQuery and dbt on infrastructure provisioned by the central data platform team, linking HR data across the employee lifecycle from Workday, Greenhouse, Qualtrics, and ServiceNow to trace how hiring decisions affect long-term engagement and retention.
  • Support and enhance the AI-powered analytics user experience.
  • Develop scalable, self-service dashboards that reduce time spent on reactive, one-off data requests.
  • Implement data governance practices, including access controls, validation, and documentation, in line with team standards for sensitive HR and compensation data.
  • Build data proficiency across the broader HR team as part of the shift to self-service.
  • Automate recurring recruiting reports to eliminate manual data wrangling.
  • Translate talent data into insights that identify pipeline bottlenecks, improve candidate experience, and improve hiring efficiency.
  • Monitor recruiting data for anomalies and build validation checks to establish one version of the truth across systems.

Desired Qualifications

  • A point of view on AI/LLM-based analytics tools and how they simplify insight delivery; direct experience implementing one is a plus.
  • A builder's approach: comfort creating solutions, frameworks, and processes with limited existing scaffolding while working within a set architectural direction.

About the Company

Elastic

Searches enterprise data and monitors systems

Elastic builds search, observability and security software for developers, IT operations teams and security analysts. Elasticsearch indexes enterprise data so applications can retrieve records, while Kibana gives teams dashboards for exploring results and investigating system activity. Customers use the tools to search business information, monitor applications and infrastructure, and investigate threats across their data. Elastic sells managed cloud services and self-managed subscriptions, with resource-based hosted pricing, usage-based serverless pricing and licenses tied to nodes and memory. Founded in 2012, Elastic lists San Francisco, California, as its headquarters.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2012

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