Top Skills That Will Get You a Data Analyst Job in 2025

If you are aiming to land a data analyst role, you probably already know the fundamentals: Python, SQL, a visualization tool like Tableau or Power BI, and Excel. But knowing these alone may not be enough to separate you from hundreds of equally qualified candidates. Based on direct conversations with recently placed data analyst candidates at Wynisco Inc., there are three additional skill sets that consistently improve your chances of getting hired — and most job seekers overlook all of them.

Why Core Skills Are Just the Starting Point

The data analyst job market is highly competitive. Hiring managers at modern companies are not only looking for someone who can write a SQL query or build a Python script — they want candidates who understand the business context in which data lives. That means knowing the tools their business already uses, and understanding how data flows between systems. The skills below are consistently requested by companies that Wynisco places candidates with, and learning even one of them can dramatically increase your interview success rate.

Skill #1: CRM Platforms — Salesforce and HubSpot

The first additional skill we strongly recommend is CRM knowledge — and ideally, hands-on experience with both Salesforce and HubSpot. If you can only learn one, start with Salesforce. But knowing both gives you a significant competitive advantage.

As a data analyst in almost any industry, you will regularly interact with CRM APIs to fetch, update, and analyze customer records. CRM data encompasses sales pipelines, marketing campaign performance, customer segments, and other high-value intelligence that directly informs business decisions.

Beyond just querying the data, companies want analysts who understand how sales and marketing funnels work. For example: How do you qualify an inbound lead and route it to the right territory, account manager, or regional team? How do you use historical data and public domain signals to score a lead's likelihood to convert? These are precisely the kinds of questions a data analyst with CRM knowledge can answer — making you far more valuable than a candidate who only knows SQL.

What to Learn in CRM for Data Analysis

• How to connect to Salesforce and HubSpot APIs using Python

• Querying CRM objects (Contacts, Leads, Accounts, Opportunities)

• Understanding lead qualification logic and sales funnel stages

• Using CRM data to build sales performance dashboards

• Combining CRM data with marketing attribution data for full-funnel reporting

Skill #2: Shopify — E-Commerce Data Integration

The second skill that can set you apart is Shopify. Hundreds of companies — from startups to enterprise brands — have moved away from custom-built e-commerce portals to Shopify as their primary platform. These businesses need data analysts who understand how Shopify works and how to extract meaningful insights from it.

Understanding Shopify's API is particularly valuable. It allows you to pull product listings, customer orders, inventory levels, and marketing performance data, then integrate that information with other business systems (such as CRM, ERP, or marketing platforms) to give stakeholders a complete picture of business performance.

If you are applying to any e-commerce company, a retailer, a DTC brand, or even a marketing agency that serves them, Shopify knowledge can be the deciding factor in whether you get the job.

What to Learn in Shopify for Data Analysts

• Shopify Admin API and Storefront API basics

• Extracting and transforming order, product, and customer data

• Connecting Shopify data to Google Sheets, BigQuery, or a data warehouse

• Building dashboards around Shopify KPIs: AOV, LTV, conversion rate, refund rate

• Automating data pipelines between Shopify and CRM or ERP systems

Skill #3: Advanced Excel — Still One of the Most Requested Skills

It might surprise you, but Excel remains one of the most requested skills in data analyst job postings — even in 2025. While bootcamps and self-study programs often rush past Excel to focus on Python and BI tools, many businesses still run their day-to-day analysis, reporting, and decision-making directly in Excel.

The difference between a basic Excel user and an advanced one is significant. Employers are not looking for someone who can just create a simple spreadsheet — they want analysts who can build dynamic models, automate repetitive tasks with macros, use Power Query to connect and transform data sources, and create clear, stakeholder-ready reports.

Do not underestimate Excel. Mastering it will make you more effective across every role you take, and in many interview processes, you will be tested on it directly.

Advanced Excel Skills Worth Learning

• Pivot Tables and Pivot Charts for rapid data summarization

• XLOOKUP, INDEX/MATCH, and dynamic array formulas

• Power Query for connecting, cleaning, and transforming data sources

• Power Pivot and data modeling with DAX

• Dashboard design for business stakeholders

• Basic VBA / macro automation for recurring reports

Frequently Asked Questions About Data Analyst Skills

What skills do you need to become a data analyst?

The core technical skills for a data analyst are Python, SQL, Excel, and a data visualization tool such as Tableau or Power BI. To stand out in the job market in 2025, it is also highly recommended to gain hands-on experience with CRM platforms like Salesforce or HubSpot, understand e-commerce data through Shopify, and develop advanced Excel proficiency beyond the basics.

Why should a data analyst learn CRM tools like Salesforce or HubSpot?

As a data analyst, you will regularly interact with CRM APIs to fetch and update customer records. CRM systems hold sales, marketing, and customer intelligence data that analysts use to generate business insights. Understanding how CRM data flows—including lead qualification, territory routing, and funnel analysis—makes you significantly more valuable to employers than a candidate who only knows core coding skills.

Why is Shopify a useful skill for data analysts?

Many companies have migrated to Shopify as their primary e-commerce platform. Data analysts who understand Shopify's API can pull product, order, and customer data, integrate it with other systems, and provide actionable insights into business performance. This is especially valuable for e-commerce brands, retailers, and DTC companies.

Is Excel still important for data analysts in 2025?

Yes — Excel remains one of the most widely used tools in business. Despite the rise of Python and BI platforms, many companies still rely on Excel for analysis, reporting, and decision-making. Advanced Excel skills such as Power Query, Power Pivot, dynamic formulas, and dashboard design continue to be in high demand among data analyst employers.

What is a sales and marketing funnel, and why does a data analyst need to understand it?

A sales and marketing funnel describes the journey a potential customer takes from first becoming aware of a product to making a purchase. Data analysts who understand funnel mechanics can analyze conversion rates, identify drop-off points, score and qualify leads, and help route them to the right sales territory or team — using CRM data, web analytics, and other sources.

The Bottom Line: What Separates Good Data Analyst Candidates From Great Ones

The data analyst job market rewards candidates who go beyond the technical checklist. Python and SQL are table stakes. What gets you hired — and what gets you promoted — is your ability to work with the tools real businesses use every day. Investing time in CRM platforms like Salesforce and HubSpot, understanding how e-commerce data works through Shopify, and mastering advanced Excel will make you a candidate that hiring managers remember.

If you have come across other skills in the market that have proven to be valuable additions for data analyst roles, share them in the comments — we'd love to hear what you're seeing.

About the Author: Sachin Rajgire is a data career advisor at Wynisco Inc., a data and analytics staffing and training firm. Wynisco has helped hundreds of candidates successfully transition into data analyst, data engineer, and business analyst roles.