ADCI
Finance
BusinessIntelligenceEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Business Intelligence Engineer at ADCI. Skills: Business Intelligence, Data Analytics, ETL, Data Modeling. Own data analytics and insights. Drive product and business decisions”
Industry & Context.
Root-cause analysis; Anomaly identification; Optimization opportunities
What They're Looking For.
Must Have
3+ years analyzing data, Redshift experience, Oracle experience, NoSQL experience, Data visualization experience, Data modeling experience, Warehousing experience, Building ETL pipelines experience, Statistical Analysis packages experience, SQL proficiency, Scripting experience (Python)
Nice to Have
AWS solutions experience, Data mining experience, ETL experience, Using databases in business environment, Large-scale, complex datasets experience
What You'll Do.
Own data analytics and insights
Drive product and business decisions
Partner with product managers
Partner with engineers
Partner with technical program managers
Partner with business stakeholders
Establish data-driven entitlements
Build scalable analytics solutions
Deliver actionable insights
Optimize financial automation processes
Advocate for data-driven decision making
Define analytics roadmap
Prioritize analytics roadmap
Contribute to product discovery
Perform scenario analysis
Perform entitlement studies
Perform exploratory data analysis
Develop metrics frameworks
Define KPI definitions
Develop measurement strategies
Ensure data alignment
Ensure data consistency
Design data pipelines
Develop automated dashboards
Develop self-service analytics tools
Conduct deep-dive analyses
Conduct root-cause analysis
Conduct bridges analysis
Conduct loss attribution analysis
Partner with data engineering teams
Decide on data quality
Decide on schema design
Decide on infrastructure
Perform statistical analysis
Identify optimization opportunities
Translate complex findings
Provide clear recommendations
Provide actionable recommendations
How You'll Work.
Team & Collaboration
Partner with product managers; Partner with engineers; Partner with technical program managers; Partner with business stakeholders; Partner with data engineering teams
Communication Scope
Actionable recommendations
Process & Methodology
Define analytics roadmap, Prioritize analytics roadmap
Full Job Description
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 Basic Qualifications: - 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 Preferred Qualifications:
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