Okta
Identity
StaffAnalyticsEngineer-Finance
Neural analysis suggests this role is
optimal for Lead candidates.
“Staff Analytics Engineer - Finance at Okta. Skills: Analytics Engineering, Data Engineering, dbt, Snowflake, Data Modeling, Semantic Layer. Drive architectural evolution of the Finance data models. Design, build, and maintain scalable data models using dbt and Snowflake”
What You'll Achieve.
Trusted, well-structured data models that reliably support Finance reporting; Consistent metric definitions across teams and tools; High-quality, well-documented datasets that enable self-service analytics; A semantic and modeling foundation that scales with the business; Data that is not only accurate for reporting, but ready to power AI and intelligent applications; The Finance data domain operates on a defined multi-quarter technical roadmap, resulting in demonstrable improvements in data platform resilience, cost-efficiency, and scalability.
Industry & Context.
solve complex challenges; Ability to navigate highly ambiguous business challenges, translating vague, complex, or competing goals from executive stakeholders into clear, actionable, and robust data solutions
What They're Looking For.
Must Have
8+ years of experience in Analytics Engineering, Data Engineering, or similar roles, at least 2 years operating in a high-impact Senior or Lead capacity, Proven track record of defining, driving, and delivering a multi-quarter technical roadmap for a critical data domain (e.g., Finance, Growth), SQL skills and experience building analytics-ready data models, Hands-on experience with dbt and Snowflake, Solid understanding of data modeling principles, including dimensional modeling and semantic design, Ability to navigate highly ambiguous business challenges, translating vague, complex, or competing goals from executive stakeholders into clear, actionable, and robust data solutions, Experience with data quality, testing, and documentation best practices
Nice to Have
Exposure to Python, R, or data processing frameworks (e.g., PySpark), Experience with BI tools such as Tableau or Looker
What You'll Do.
Drive architectural evolution of the Finance data models
and maintain scalable data models using dbt and Snowflake
Define and standardize core Finance metrics
Establish consistent modeling patterns
and semantic clarity across datasets
Contribute to a shared semantic layer that supports both analytics and AI use cases
Define the strategy for data readiness and consumption by AI/LLMs
well-governed datasets for use with Snowflake Cortex and Snowflake Intelligence
Enable structured data foundations that support LLM-powered use cases
and intelligent applications
Implement robust testing
and documentation practices in dbt
Apply data governance best practices
Define and own the multi-quarter technical roadmap for the Finance data domain
and cross-functional stakeholders to translate business needs into data solutions
Support self-service analytics by building intuitive
Contribute to scalable data workflows that balance immediate business needs with long-term maintainability
Work within an agile environment
contributing to planning
and continuous improvement
How You'll Work.
Team & Collaboration
Partner closely with Finance stakeholders, Data Analysts, and Data Engineers; Partner across teams to establish clear ownership and accountability for data assets; Partner with Finance, Analysts, and cross-functional stakeholders to translate business needs into data solutions; work across technical and business teams
Communication Scope
communication skills; ability to work across technical and business teams
Process & Methodology
Define and own the multi-quarter technical roadmap for the Finance data domain, aligning data architecture decisions with executive business objectives and anticipating future growth and regulatory needs, planning, prioritization
Full Job Description
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta At Okta, our mission is to enable any organization to use any technology, making the world a more secure and connected place. We are the leading independent provider of identity for the enterprise. We work with an incredible array of customers, from the largest enterprises to the most innovative startups, to help them securely connect their people to technology. As we enter a new phase of growth, our AI and data capabilities will be a critical pillar of our success, powering secure and scalable products that serve both our customers and employees. The Opportunity We are seeking a Staff Analytics Engineer to support Finance by building reliable, well-modeled, and trusted data for reporting, decision-making, and emerging AI use cases. This role sits at the intersection of business context and technical execution. You will design scalable data models, define consistent business logic, and help establish a strong semantic foundation that enables both human analytics and machine-driven intelligence. You will partner closely with Finance stakeholders, Data Analysts, and Data Engineers to ensure data is accurate, consistent, and easy to consume; whether through dashboards, self-service exploration, or AI-powered workflows. What You’ll Do Data Modeling & Semantics Drive architectural evolution of the Finance data models, evaluating and implementing new design patterns to ensure long-term scalability and resilience. Design, build, and maintain scalable da
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