Analytics Engineer

• Develop, modify, and maintain dashboards and reports in Power BI, Tableau, Databricks AI/BI, Looker, or similar BI tools
• Translate business requests submitted through the ticketing system into accurate and actionable data visualizations
• Ensure consistency in definitions, metrics, and data logic across reports
• Optimize queries and dashboards for performance and clarity
• Document logic and assumptions behind key metrics and dashboards
• Create and maintain database views, derived tables, and other analytical objects
• Perform data modeling and transformation tasks for reliable downstream reporting
• Troubleshoot data discrepancies and validate data accuracy across systems
• Collaborate on data structure and warehouse organization improvements
• Deliver accurate, well-documented dashboards within agreed SLAs
• Produce clean, reusable SQL objects for long-term reporting needs
• Improve clarity and consistency in metric definitions and reduce reporting-request back-and-forth
• Collaborate closely with cross-functional teams and support more junior team members

Analytics Engineer, BI

• Own the company-wide data roadmap for product, marketing, operations, and finance
• Prioritize platform health and stakeholder needs, present and defend the roadmap, and re-plan as the business changes
• Build automated monitoring for source data, pipelines, and reports
• Detect upstream schema and source changes before downstream breakage and run incidents to resolution
• Maintain data lineage and impact analysis from production source through warehouse models to dashboards
• Establish data contracts and integrate impact assessment into engineering change review
• Administer Lightdash, including workspace structure, permissions, certification, naming, rollout, enablement, query performance, and warehouse costs
• Extend and govern the semantic layer with one controlled definition per metric
• Govern Segment event tracking, including event review, catalog maintenance, naming, property dictionary, lifecycle, and drift detection
• Govern AI data access and keep the warehouse documented, consistent, safe, and AI-legible
• Manage data security and privacy, including access controls, PII handling, retention, and periodic access reviews
• Build documentation, ownership models, and review loops that make governance sustainable
• Start as an individual contributor and later hire and manage a Lead Analytics Engineer

Analytics Engineering Manager, Data Platform – Governance

• Own the company-wide data roadmap and prioritize platform investments
• Build automated data quality and freshness monitoring across source data, pipelines, and reports
• Manage data lineage and impact analysis from production sources through warehouse models to dashboards
• Administer Lightdash, including workspace structure, permissions, certification, naming, rollout, enablement, query performance, and warehouse costs
• Extend and govern the semantic layer with one official definition per metric
• Govern Segment event tracking, including event standards, ownership, property dictionaries, review lifecycle, and drift detection
• Govern data access for AI tools and maintain an AI-legible warehouse
• Manage data security, PII handling, retention, and periodic access reviews under US state privacy laws
• Establish documentation, ownership models, and review loops for sustainable governance
• Lead incidents to resolution and connect production change review with downstream impact assessment
• Start as a solo contributor and later hire and manage a Lead Analytics Engineer

• Controlar el proceso de asignación de staffing de Engineering, asegurando su calidad y correcto registro en herramientas institucionales
• Explotar datos para generar indicadores y métricas que faciliten la toma de decisiones del proceso de staffing de ingeniería
• Diseñar y desarrollar herramientas para centralizar información, optimizar procesos y asegurar la calidad de los registros
• Diseñar planes de capacitación y gestionar estructuras de trabajo en Jira para equipos multidisciplinarios
• Garantizar el seguimiento de proyectos mediante reportes periódicos de avance
• Garantizar la asignación de personal de ingeniería en tiempo y forma
• Automatizar y mejorar los procesos de demanda y staffing
• Diseñar planes de formación en el uso de Jira basados en roles Agile

Especialista en Análisis de Datos – Proyectos

• Drive the GTM data roadmap to build scalable, durable data products
• Build and maintain data pipelines and marts powering company-wide GTM metrics, including headcount, quota attainment, and pipeline
• Build reliable dashboards tracking core metrics and delivering insights company-wide
• Collaborate with GTM analyst teams to train and enable them on datasets and data tools
• Write documentation and tutorials
• Work across the full analytics stack, from ad hoc analysis and reports to pipeline architecture
• Build semantic models and run evaluations for AI tools that let sales operators query business data in natural language
• Use AI-assisted development tools while maintaining clean, maintainable code, models, and documentation
• Communicate complex data concepts through technical specifications, dashboards, and presentations to align teams on metrics and definitions
• Report to the Director of Business Intelligence as part of a centralized global analytics and data engineering team

Senior Analytics Engineer – GTM

• Design, build, and maintain complex data models supporting critical operational and reporting needs.
• Work with internal and external teams to implement data-driven solutions to improve care delivery and business value.
• Develop and implement data quality and integrity standards to ensure accurate and reliable data.
• Conduct data exploration and investigation to identify insights and patterns in healthcare and business systems data.
• Develop and maintain data infrastructure, including data pipelines, databases, and data warehousing solutions.
• Develop, automate, and maintain reports and dashboards that provide clear, actionable insights to stakeholders across the organization.

Senior Analytics Engineer – Health Care

• Own PayJoy's Unity Catalog governance model, including catalog and schema architecture, tagging and metadata standards, lineage, grants, and PII controls
• Define and operate data trust standards, including tiered certification, service-level objectives, alert detection quality, and retirement of duplicate or abandoned models
• Own the governed semantic layer and transformation development loop, including conformed dimensions, canonical entity keys, and unified definitions for cross-functionally consumed measures
• Establish experimentation practices and own the measurement substrate, including experiment metric definitions, exposure tables, guardrail metrics, and readout correctness
• Advise Product Engineering on tooling selection, statistical approach, and instrumentation architecture
• Deliver scoped enablement projects whose primary output is a reusable pattern