Business Intelligence Analyst, FinOps IN BP

We're seeking an experienced Business Intelligence Engineer to design, develop, and maintain scalable data solutions that drive business decisions. You'll work closely with business stakeholders, data engineers, and analysts to transform complex data into actionable insights. Data Architecture & Development

• Design and implement data models, ETL processes, and reporting solutions
• Create and maintain scalable data pipelines
• Develop automated reporting systems and dashboards

Business Partnership

• Partner with business teams to understand reporting requirements
• Translate business needs into technical specifications
• Provide technical guidance to junior team members
• Lead technical discussions with stakeholders

Analytics & Reporting

• Build complex SQL queries and stored procedures
• Develop interactive dashboards using visualization tools (Tableau/PowerBI)
• Create automated alert systems for business metrics
• Design and implement A/B testing frameworks

• Bachelor's degree or above in computer science, computer engineering, or related field, or Associate's degree or above
• 2+ years of business intelligence and analytics experience
• Knowledge of SQL and VBA at an advanced level
• Experience with business intelligence (BI) tools such as Tableau, Quicksight, Power BI and CRM Salesforce
• Experience with AWS, Azure, or Google Cloud technology
• Knowledge of data warehousing and data modeling
• Experience that includes strong analytical skills, attention to detail, and effective communication abilities
• Knowledge of presentations and whiteboarding skills with a high degree of comfort speaking with internal and external executives, IT management, and developers
• Experience in project management disciplines including scope, schedule, budget, quality, along with risk and critical path management
• Can work proactively and independently, meet deadlines, and deliver on projects and tasks, * Experience with agile or other program management methodologies
• Knowledge of machine learning approaches and algorithms
• Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
• Knowledge of quantitative data analysis and statistics
• Industry-specific knowledge (e.g., retail, finance)