BI Engineer
Builds the dashboards, reports, and data models that give revenue leaders a clear, real-time view of pipeline health, performance, and trends.
Common Tools
The tech stack for this discipline
Metabase
BI/AnalyticsAn open-source, self-service analytics tool designed for business users who need to query data and build dashboards without writing SQL, using a simple question-and-answer interface.
Used for
RevOps teams at startups and mid-market companies use Metabase to democratize access to revenue data, allowing non-technical sales and success teams to self-serve pipeline and account health reports.
BigQuery
Data WarehouseGoogle Cloud's serverless, highly-scalable data warehouse that uses SQL and supports petabyte-scale analytics with built-in machine learning capabilities via BigQuery ML.
Used for
RevOps teams at Google Cloud-native organizations use BigQuery to warehouse event streams, marketing touchpoints, and CRM exports for large-scale pipeline and attribution analysis without managing infrastructure.
Sigma
BI/AnalyticsA cloud-native BI platform that gives business analysts a spreadsheet-like interface directly on top of a cloud data warehouse, enabling familiar analysis at warehouse scale.
Used for
RevOps teams use Sigma to let revenue analysts explore warehouse-scale data with Excel-like ease — building ad-hoc analyses, deal-level inspections, and financial models without writing SQL or waiting for BI team queues.
Snowflake
Data WarehouseA cloud-native data warehouse platform that separates storage from compute, enabling organizations to store and query massive volumes of structured and semi-structured data across multiple cloud providers.
Used for
RevOps teams use Snowflake as the central analytical layer where CRM, marketing, product, and financial data converge, enabling cross-functional revenue analytics that no single source system can provide.
Power BI
BI/AnalyticsMicrosoft's self-service business intelligence suite that connects to hundreds of data sources and allows users to build interactive reports and dashboards within the Microsoft ecosystem.
Used for
RevOps teams embedded in Microsoft-heavy enterprises use Power BI to build revenue dashboards that pull from Dynamics CRM, Excel, Azure SQL, and SharePoint without requiring a separate BI platform.
Tableau
BI/AnalyticsAn enterprise business intelligence and data visualization platform that enables users to build interactive dashboards and reports by connecting to virtually any data source.
Used for
RevOps teams use Tableau to build executive pipeline dashboards, cohort analyses, and forecast views by connecting directly to Salesforce or warehouse data, enabling self-service analytics across revenue functions.
Looker
BI/AnalyticsA Google Cloud business intelligence platform built around a semantic layer (LookML) that defines business metrics once and makes them consistent across all reports and data consumers.
Used for
RevOps teams use Looker to define canonical revenue metrics (ARR, pipeline coverage, win rate) in LookML once, ensuring every team across the business uses the same definitions when querying revenue data.
Core Skills
What practitioners do day-to-day
Data Modelling
TechnicalThe ability to design logical representations of business data — defining entities, relationships, grain, and hierarchies — that accurately represent revenue processes and support reliable analytics.
Business outcome
Well-designed data models ensure metrics are calculated consistently, data is non-duplicated, and analytical queries run accurately — giving every team a shared, trustworthy view of revenue.
Revenue Forecasting
AnalyticalThe ability to build, maintain, and improve processes and models that predict future revenue — combining pipeline analysis, historical patterns, rep judgement, and AI signals into a single trusted number.
Business outcome
Accurate revenue forecasting allows the business to make confident hiring, investment, and spending decisions — reducing the risk of missed targets or over-commitment.
SQL
TechnicalProficiency in Structured Query Language for querying, transforming, and analysing data stored in relational databases and cloud warehouses — the most fundamental analytical skill in RevOps.
Business outcome
SQL fluency allows RevOps practitioners to answer any data question independently — without depending on a data team — enabling faster, more accurate decision-making across all revenue functions.
Dashboard Design
AnalyticalThe skill of designing clear, actionable visual dashboards that translate complex revenue data into insights decision-makers can act on — covering layout, chart selection, metric hierarchy, and interactivity.
Business outcome
Well-designed dashboards reduce the time revenue leaders spend in data extraction and preparation, enabling faster decision cycles, more consistent review rhythms, and broader data literacy across the org.