Tools, Frameworks & Implementation Proficiency Topics
Practical proficiency with industry-standard tools and frameworks including project management (Jira, Azure DevOps), productivity tools (Excel, spreadsheet analysis), development tools and environments, and framework setup. Focuses on hands-on tool expertise, configuration, best practices, and optimization rather than conceptual knowledge. Complements technical categories by addressing implementation tooling.
Aggregation Functions and Group By
Fundamentals of aggregation in Structured Query Language covering aggregate functions such as COUNT, SUM, AVG, MIN, and MAX and how to use them to calculate totals, averages, minima, maxima, and row counts. Includes mastery of the GROUP BY clause to group rows by one or more dimensions such as customer, product, region, or time period, and producing metrics like total revenue by month, average order value by product, or count of transactions by date. Covers the HAVING clause for filtering aggregated groups and explains how it differs from WHERE, which filters rows before aggregation. Also addresses related topics commonly tested in interviews and practical problems: grouping by multiple columns, grouping on expressions and date truncation, using DISTINCT inside aggregates, handling NULL values, ordering and limiting grouped results, using aggregates in subqueries or derived tables, and basic performance considerations when aggregating large datasets. Practice examples include calculating monthly revenue, finding customers with more than a threshold number of orders, and identifying top products by sales.
Customer Relationship Management Administration
Administration and configuration of Customer Relationship Management platforms such as Salesforce, HubSpot, and Pipedrive. Candidates should understand core Customer Relationship Management concepts and the underlying data model, including accounts, contacts, leads, opportunities, custom objects, record types, relationship types such as lookups and master detail, and how records relate and flow through business processes. Expect hands on configuration and customization skills: creating and modifying objects and fields, page layouts, record types, validation rules, field dependencies, assignment and routing rules, automation using workflows and flows, and basic programmatic extensions and deployments. Reporting and dashboard capabilities are important: building and filtering reports, designing dashboard components, using summary and formula fields, scheduling and exporting reports, and constructing reports that support revenue metrics such as opportunity amount, stage, close date, probability, and custom revenue fields. Candidates should be able to explain data quality and governance practices including field mapping, import and export strategies, deduplication, data validation, maintenance, and practices to preserve reporting accuracy. Security and permission models should be understood at a high level, including profiles, roles, permission sets, sharing rules, and field level security and how those choices affect visibility and access. Finally, candidates should be prepared to discuss integration and data flow topics such as common integration patterns and middleware, batch versus real time synchronization, how external systems feed or consume Customer Relationship Management data, platform specific limitations and trade offs when designing scalable solutions, and examples of implementations or optimizations they have performed.
CRM Systems & Sales Technology Basics
Practical familiarity with at least one CRM platform (preferably Salesforce given its FAANG prevalence), basic understanding of CRM data structure, record management, and how CRM data feeds into reporting and analysis. Awareness of other common sales tools in the tech stack (Slack, email platforms, automation tools).
Salesforce and Sales Technology Management
Hands on experience configuring customizing and administering customer relationship management platforms such as Salesforce and the broader sales technology stack. This includes designing clean data models for accounts contacts opportunities leads and custom objects; creating fields page layouts record types and validation rules; implementing declarative automation such as workflow rules process flows and scheduled processes; defining security and access controls including profiles permission sets and sharing models; establishing data quality controls and master data management practices to prevent duplicates and missing fields; architecting integrations using application programming interfaces webhooks middleware and batch integration patterns including error handling retries and monitoring; designing extract transform load and synchronization processes to maintain a single source of truth; managing development test and production environments and release processes with change management and testing practices; and driving user adoption through training documentation stakeholder engagement and enablement programs. Interviewers evaluate the ability to translate business requirements into technical configuration and integration decisions that preserve data integrity scalability and forecast reliability.
Common CRM Platforms and Their Characteristics
Understand major CRM platforms: Salesforce (enterprise, highly customizable, high complexity), HubSpot (SMB-friendly, easier to use), Microsoft Dynamics (enterprise, often used with other Microsoft tools), Pipedrive (sales-first focus). Know basic differences in ease of use, cost, customization, and typical customers. This isn't about being an expert in each, but recognizing that different tools serve different needs.
CRM and Sales Technology Implementation
End to end skills for selecting, implementing, configuring, integrating, and optimizing customer relationship management platforms and sales automation tools. Coverage includes platform proficiency and configuration patterns, custom object and field architecture, workflow and automation design, permission and security models, integration and API patterns, data pipelines and single source of truth design, data standards and validation rules, testing and release management, implementation lifecycle planning, vendor evaluation, change management and enablement strategies, training and adoption measurement, operational troubleshooting, and continuous optimization to drive sales productivity and reporting accuracy.
Spreadsheet and Data Manipulation
Practical proficiency with spreadsheet tools such as Microsoft Excel to clean, transform, and prepare data for analysis and reporting. Core skills include using pivot tables to summarize and slice data, lookup functions such as VLOOKUP and INDEX MATCH to reconcile and join datasets, building formulas for calculated fields, text and date transformation, conditional formatting, data validation, filtering and sorting, and using extract transform and load tooling available in spreadsheets to automate routine transformations. Comfortable importing and reconciling data exports from customer relationship management systems such as Salesforce, diagnosing inconsistencies, and producing clear tables and charts to support analytical recommendations.
Date and Time Operations
Tests practical skills for working with dates and times in analysis and operations. Candidates should be comfortable with date filtering, date comparisons, relative date ranges such as last n days or rolling windows, fiscal period calculations, and basic date functions used in queries and reporting. Interviewers assess ability to translate business reporting needs into correct date logic, handle edge cases such as time zones and inclusive versus exclusive ranges, and apply these skills in contexts like sales pipeline aging, period over period comparisons, and performance windows.
Spreadsheet Analysis and Modeling
Hands on skills for analyzing, modeling, and reporting data using spreadsheet software and lightweight tabular tools. Candidates should demonstrate data organization and cleaning techniques, proficiency with formulas and functions for calculations and conditional logic, and use of lookup and aggregation methods. Expect fluency with pivot tables for summarization and segmentation, charting and other visualizations, and building simple dashboards and reports. Important skills include correct use of absolute and relative references, efficient spreadsheet layout for accuracy and collaboration, conditional formatting, and strategies for working with large datasets. Candidates may also be expected to perform basic statistical measures such as averages medians and distribution checks, compute growth and conversion metrics, and automate repetitive tasks using built in scripting or macro features. Interviewers frequently assess the ability to derive actionable insights from tabular data quickly and accurately, often under time constraints.