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As Business Intelligence Engineer, you will have end-to-end ownership of data analytics and insights that drive product and business decisions for the FinAuto team. In this role, you will partner with product managers, engineers, technical program managers, and business stakeholders to establish data-driven entitlements, build scalable analytics solutions, and deliver actionable insights that optimize financial automation processes.
Key job responsibilities
Analytics Leadership:
Listen to and advocate for data-driven decision making across the organization
Define and prioritize the analytics roadmap (metrics, dashboards, deep-dive analyses, self-service tools)
Contribute to product discovery via scenario analysis, entitlement studies, and exploratory data analysis
Develop metrics frameworks, KPI definitions, and measurement strategies
Ensure data alignment and consistency across all teams and reporting layers
Technical Execution:
Design and build scalable data pipelines, ETL processes, and data models
Develop automated dashboards and self-service analytics tools for stakeholders
Conduct deep-dive analyses including root-cause analysis, bridges, and loss attribution
Partner with data engineering teams on data quality, schema design, and infrastructure decisions
Perform statistical analysis and modeling to identify trends, anomalies, and optimization opportunities
Translate complex analytical findings into clear, actionable recommendations for technical and non-technical audiences
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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Job ID: 144884851
