ADCI

Finance

BusinessIntelligenceEngineer

₹19–28L ~AI est. Bengaluru, Karnataka, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“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.

Finance
Problems you'll solve

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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