Business Intelligence Data Analytics Engineer

Overview

Model N is  seeking a highly skilled Finance Data Analyst to join our Business Intelligence (BI) team in India. This role partners closely with U.S. Finance and cross-functional teams to deliver data-driven insights that support financial planning, forecasting, and performance management. The ideal candidate combines strong analytical, technical, and business acumen with a passion for transforming data into clear, actionable insights.

Responsibilities

Partner with Finance and cross-functional teams to translate business questions into clear, data-driven insights that support planning, forecasting, and performance management. Execute end-to-end analytics projects: define requirements, explore financial and operational datasets, build data models, and deliver insights through dashboards, reports, and presentations. Develop, enhance, and maintain Power BI dashboards and reporting assets to track key financial and go-to-market metrics (e.g., pipeline coverage, ARR/NRR, revenue retention, quota attainment, customer health). Analyze customer, revenue, and product usage data to identify trends related to growth, churn, expansion, pricing, and performance that inform strategic decision-making. Support development of predictive or statistical models (e.g., retention/expansion propensity, forecast drivers, segmentation) using Python or other analytical tools. Validate data accuracy and reconcile financial and operational metrics across CRM, ERP, and data warehouse sources, partnering closely with BI/IT and Data Engineering teams. Use SQL, Python, and Azure Fabric (or similar cloud data tools) to prepare datasets, automate reporting workflows, and scale financial analytics processes. Ensure alignment on KPI definitions, data sources, and metric governance across Finance and GTM teams to drive consistent reporting and performance transparency. Continuously improve analytics workflows, data visualization standards, and self-service reporting capabilities to enable efficient, insight-driven decision support across the organization.

Requirements 5–8 years of experience in business intelligence, data analytics, or a related role. Proven ability to deliver actionable insights from large, complex, and diverse datasets. Experience working cross-functionally to support strategic initiatives. Bachelor’s degree in a quantitative, technical, or business field (e.g., Statistics, Mathematics, Economics, Computer Science, Data Science, Business Analytics). Master’s degree preferred in Business Analytics, Data Science, or a related discipline.

Technical Skills Advanced proficiency in Power BI, DAX, data modelling, and dashboard design. Strong proficiency in Python for data analysis, statistical modelling, and automation. Experience working with Azure Fabric or other modern cloud-based data platforms. Strong SQL skills for querying, joining, and transforming structured data. Understanding of data warehousing concepts (e.g., star schema, dimensional modelling); experience with platforms like Azure Synapse, Snowflake, or Redshift. Exposure to CRM platforms (e.g., Salesforce) and familiarity with version control tools (e.g., Git).

Analytical & Business Acumen Solid foundation in descriptive and predictive analytics, including statistical methods and machine learning. Ability to integrate, clean, and analyze data from disparate systems. Skilled in translating complex data into clear narratives, actionable insights, and strategic recommendations.

Job Responsibilities •

Design, build, and maintain scalable data pipelines using Fivetran to ingest data from Salesforce, ERP, and other business systems into Snowflake.

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Own the data transformation layer between raw ingested sources and analytics-ready datasets, ensuring models are clean, tested, documented, and aligned to Finance and GTM reporting needs.

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Build and maintain Tableau dashboards and reporting assets to track key financial and go-to-market metrics, including pipeline coverage, ARR/NRR, revenue retention, quota attainment, and other GTM activities.

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Partner with Finance and cross-functional stakeholders to translate business questions into data models, metrics definitions, and dashboard solutions.

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Validate data accuracy and reconcile financial and operational metrics across source systems (CRM, ERP, and other systems of record) and the Snowflake data warehouse.

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Manage data warehouse objects in Snowflake, including schema design, virtual warehouse configuration, role-based access controls, and query optimization.

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Define and enforce KPI definitions, data source documentation, and metric governance to drive consistent reporting across Finance and GTM teams.

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Analyze customer, revenue, and product usage data to surface trends related to growth, churn, expansion, pricing, and performance.

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Continuously improve analytics workflows, documentation standards, and self-service reporting capabilities to scale insight delivery across the organization.

Job Qualification •

4–7 years of experience in analytics engineering, business intelligence, or a related data role.

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Hands-on experience with Snowflake and Fivetran in a production environment.

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Strong SQL skills for querying, joining, and transforming structured data across complex schemas.

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Experience building and maintaining Tableau dashboards and data sources.

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Familiarity with CRM data structures, particularly Salesforce objects and reporting.

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Experience working cross-functionally with Finance, Ops, or GTM teams to support data and reporting needs.

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Bachelor’s degree in a quantitative, technical, or business fields (e.g., Statistics, Mathematics, Economics, Computer Science, Data Science, Business Analytics). Master’s degree preferred.

Technical Skills

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Snowflake: schema design, virtual warehouse management, RBAC, query optimization, and cost monitoring.

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Fivetran : connector configuration, sync scheduling, schema change handling, and MAR management.

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Tableau : advanced dashboard design, calculated fields, LOD expressions, data source management, and Tableau Server/Cloud publishing.

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SQL : advanced querying across Snowflake; window functions, CTEs, and performance tuning.

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Salesforce: familiarity with standard and custom objects, SFDC data exports, and CRM reporting structures.

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Git: version control for analytics codebases.

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Python (preferred) for data analysis, automation, and supplemental data processing tasks.

Analytical & Business Acumen

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Solid understanding of SaaS business metrics (ARR, NRR, churn, pipeline coverage, quota attainment) and how they flow through financial and GTM reporting.

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Ability to integrate, clean, and analyze data from disparate source systems into a coherent, governed data model.

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Skilled in translating complex data into clear narratives, actionable insights, and strategic recommendations for Finance and executive audiences.