Okta22.04.2026
Staff Data Analyst
Bengaluru
Обязанности
- 01Drive architectural evolution of the Finance data models, evaluating and implementing new design patterns to ensure long-term scalability and resilience
- 02Design, build, and maintain scalable data models using dbt and Snowflake
- 03Define and standardize core Finance metrics (e.g., revenue, ARR, billing) with clear, governed logic
- 04Establish consistent modeling patterns, naming conventions, and semantic clarity across datasets
- 05Contribute to a shared semantic layer that supports both analytics and AI use cases
- 06Define the strategy for data readiness and consumption by AI/LLMs, ensuring that governance and semantic clarity standards meet the requirements for trustworthy and responsible automated decision-making
- 07Prepare high-quality, well-governed datasets for use with Snowflake Cortex and Snowflake Intelligence
- 08Ensure data is context-rich, well-documented, and aligned with business meaning to improve AI accuracy and trust
- 09Implement robust testing, validation, and documentation practices in dbt
- 10Ensure consistency across reports and dashboards through shared definitions and reusable models
- 11Apply data governance best practices, including access controls, lineage, and auditability
- 12Partner across teams to establish clear ownership and accountability for data assets
- 13Define 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
- 14Partner with Finance, Analysts, and cross-functional stakeholders to translate business needs into data solutions
- 15Support self-service analytics by building intuitive, reusable datasets
- 16Contribute to scalable data workflows that balance immediate business needs with long-term maintainability
- 17Work within an agile environment, contributing to planning, prioritization, and continuous improvement
- 18Demonstrate an AI-first mindset, thinking beyond data models and dashboards to how data can power intelligent systems and decision-making
- 19Understand the importance of well-modeled, well-documented, and semantically clear data for AI and LLM-based use cases
- 20A level of comfort leveraging AI-assisted workflows to improve productivity, code quality, and consistency
- 21Curiosity for emerging capabilities in platforms like Snowflake Cortex and Snowflake Intelligence, and how they can be applied to Finance analytics
Требования
- 018+ years of experience in Analytics Engineering, Data Engineering, or similar roles, with at least 2 years operating in a high-impact Senior or Lead capacity
- 02Proven track record of defining, driving, and delivering a multi-quarter technical roadmap for a critical data domain (e.g., Finance, Growth)
- 03Mentorship, raising the technical bar, establishing organization-wide standards for dbt/SQL quality and CI/CD
- 04Strong SQL skills and experience building analytics-ready data models
- 05Hands-on experience with dbt and Snowflake
- 06Solid understanding of data modeling principles, including dimensional modeling and semantic design
- 07Ability to navigate highly ambiguous business challenges, translating vague, complex, or competing goals from executive stakeholders into clear, actionable, and robust data solutions
- 08Familiarity with SaaS metrics and Finance data (e.g., ARR, revenue recognition, billing)
- 09Experience with data quality, testing, and documentation best practices
- 10Exposure to Python, R, or data processing frameworks (e.g., PySpark) is a plus
- 11Experience with BI tools such as Tableau or Looker
- 12Strong communication skills and ability to work across technical and business teams