Staff Business Intelligence Engineer
New
IndiaFull-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 7+ years
- Required Skills
- PythonSQLSnowflakeTableauData modelingdbtLooker
Requirements
- 7+ years of experience in business intelligence, data analytics, or related fields, including senior/staff-level responsibilities.
- Strong experience managing enterprise BI tools such as Tableau, Looker, Superset, or similar platforms.
- Advanced SQL skills with strong experience in data modeling and modern data warehouses (e.g., Snowflake, Athena, or equivalent).
- Proven track record of building self-service analytics solutions that reduce dependency on centralized data teams.
- Experience working directly with business stakeholders to define requirements and deliver scalable analytics products.
- Strong understanding of data governance, metric definition, and semantic layer design.
- Familiarity with dbt or similar transformation frameworks is a plus.
- Experience with Python for analytics automation or data workflows is desirable.
- Exposure to AI/LLM-based analytics solutions or agentic AI systems is highly preferred.
- Strong communication, stakeholder management, and problem-solving skills.
Responsibilities
- Own and evolve enterprise BI platforms, ensuring scalability, performance, governance, and long-term roadmap alignment.
- Design and build reusable dashboards and reporting solutions that deliver actionable insights across multiple business functions.
- Architect and implement self-service analytics solutions, enabling non-technical users to access and interpret data independently.
- Develop agentic AI-driven analytics capabilities, including natural language querying and automated insight generation.
- Collaborate with data engineering and business teams to translate requirements into scalable, well-documented data products.
- Define and enforce BI best practices, including semantic layer design, metric standardization, and data governance frameworks.
- Partner with stakeholders across Finance, Sales, Marketing, and Operations to identify high-impact analytics opportunities.
- Ensure data quality, consistency, and accessibility across BI systems and reporting layers.
- Drive continuous improvement of BI tools, processes, and user adoption across the organization.
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