Build and run experiments across the signup, onboarding, pricing, and marketing sites to drive growth and revenue.
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Compensation
Competitive salary
Stock options
Responsibilities
Build a steady cadence of experiments across signup, onboarding, pricing, and the marketing site, from hypothesis to instrumentation to readout.
Instrument the paid funnel end to end so our paid team can see what happens after the click, including on mobile.
Build and maintain the glue between the product and our growth stack: event tracking, RudderStack pipelines, Customer.io triggers, enrichment, and reverse ETL.
Contribute to the marketing site and landing page infrastructure so marketing can launch pages, campaigns, and tests quickly without waiting on core product engineering.
Partner with growth stakeholders to decide what is worth building, and push back with data when it isn't.
The Senior Data Analyst supports the management, analysis, quality control, visualization, and delivery of data for large facility condition assessment, asset management, and capital planning programs.
Responsibilities
Manage, organize, analyze, and validate large datasets associated with facilities, building systems, assets, deficiencies, costs, lifecycle information, and capital improvement needs.
Develop and maintain data structures, data models, relationships, naming conventions, and standardized data requirements for asset management projects.
Perform data cleaning, transformation, reconciliation, and quality control to identify missing, duplicate, inconsistent, or anomalous information.
Develop automated and repeatable processes for data validation, analysis, transformation, and reporting.
Use SQL and other analytical tools to query, manipulate, combine, and analyze data from multiple sources.
Develops innovative software solutions supporting complex transportation and infrastructure projects, collaborating with engineers, planners, and planners.
Responsibilities
Collaborate with technical leads, engineers, and stakeholders to translate business and project requirements into scalable software solutions.
Design, develop, test, and maintain web-based and desktop applications that support transportation planning, traffic engineering, transit, and infrastructure projects.
Build new features and enhance existing applications while ensuring performance, reliability, and user experience.
Develop intuitive user interfaces and workflows that simplify complex engineering and geospatial processes.
Troubleshoot, debug, and optimize applications to support project teams and clients across a variety of transportation programs.
The Applied AI Site Reliability Engineer focuses on the reliability, performance, and operational integrity of high-visibility products and platforms. The role involves cloud platform engineering, observability, and applied AI fluency to operate AI and agentic workloads.
Compensation
A reasonable estimate of the current range is $69,400 to $127,900.
Responsibilities
Drive a culture of accountability for reliability, performance, and cost outcomes measured in SLOs and error budgets.
Operate products, platforms, and environments to meet SLOs within budget.
Serve as technical advocate for production reliability and operability.
Participate in design of observability, performance, and resilience testing, and operational tooling.
Maintain operational integrity of production and pre-production environments.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $102,500 to $188,900.
Responsibilities
Operate the products, platforms, and environments to meet SLOs
Lead design of observability, performance and resilience testing
Own admission of systems into production
Maintain operational integrity of production and pre-production environments
Build and operate production observability dashboards and alerting
Requirements
Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $113,100 to $208,300
Responsibilities
Operate production systems to meet SLOs and error budgets
Design and implement observability, performance, and resilience testing
Own admission of systems into production
Lead blameless postmortems and continuous improvement
Collaborate with cross-functional teams to set production standards
Requirements
Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
A leadership-level engineering role focused on the reliability, performance, and operational integrity of high-visibility ServiceNow platforms, specifically integrating applied AI and agentic workloads.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113,100 to $208,300.
Responsibilities
Embrace a culture of accountability for reliability, performance, and cost outcomes measured in SLOs and error budgets
Serve as technical advocate for production reliability and operability
Set production standards and lead design of observability, performance, resilience testing, and operational tooling
Maintain accountability for operational integrity of production and pre-production environments
Build and operate production observability (dashboards, SLO-driven alerting)
Requirements
Bachelor’s degree in computer science
software engineering
data science
machine learning
Nice to have: ServiceNow Certified System Administrator (CSA)
Lead Applied AI Site Reliability Engineer II responsible for reliability, performance, and operational integrity of high-visibility products and platforms.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $113,100 to $208,300.
Responsibilities
Operate production systems to meet SLOs and error budgets
Design and implement observability, performance, and resilience testing
Own admission of systems into production
Lead technical advocacy for reliability and operability
Mentor and guide team members
Requirements
Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
Use analytical skills to improve business by turning complex data sets into useful information to solve global challenges across private and public sectors using machine learning and artificial intelligence advances.
Compensation
The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD).
Responsibilities
Work closely with customers to understand questions and needs
Dig into data-rich environments to find information puzzle pieces
Apply analytical skills and tools/frameworks to turn disparate data points into objective answers
Provide customers with a deep understanding of their data and how to use it
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