90,752 Verified Data Analyst Jobs (October 2026)
Data analytics jobs in October 2026 can span analyst, reporting, business intelligence, product analytics, and operations-focused roles, with postings often centered on SQL, dashboards, data quality, and stakeholder reporting. Expect a mix of remote, hybrid, and on-site openings across teams that need clearer metrics and better decision support. Create an account to explore the full job feed and auto-apply with LiftmyCV AI Agent.
Data Analytics & Customer Insights Analyst
On-siteJoin OCBC as a Data Analytics & Customer Insights Analyst, where you'll play a crucial role in driving a data-driven culture to enhance customer experience. Collaborate with diverse teams and leverage cutting-edge analytics tools to inform strategic…
Posted 4 days ago
Senior Data Analyst, Power BI Developer
On-siteIntact Financial Corporation is seeking a Senior Data Analyst and Power BI Developer for a 14-month temporary mandate. This role involves collaborating with AI and Operations teams to design dashboards that improve user experience and business…
Posted 2 weeks ago
Data Analytics, Analyst
On-siteWork Flexibility: Hybrid What you will do: Performing Data engineering via development collaboration between various databases, Web Apps, Power Apps, enterprise platforms, machine learning models. Good know-how in Power BI, Power Apps,…
Posted 1 week ago
Data & Analytics Analyst
On-siteJoin Baird as a Data & Analytics Analyst in Global Investment Banking Technology Solutions, where you'll translate data into actionable insights. You will be responsible for enhancing Power BI reports, managing the Power BI Service environment, and…
Posted 3 weeks ago
Digital Product Data Analyst
On-siteThe Digital Product Data Analyst at Apex Group plays a crucial role in enhancing product performance and user adoption for digital finance platforms. This position involves collaborating with various stakeholders to analyze data trends, develop KPIs,…
Posted 3 weeks ago
Customer Insight Analyst
On-siteCorpay is looking for a Customer Insights Analyst for its Fleetcore division in Prague, Czech Republic. The role involves analyzing customer behavior, developing analytical models, and driving data-driven decision-making to enhance customer…
Posted 1 week ago
Customer Insight Analyst
On-siteFinnair seeks a Customer Insight Analyst to enhance customer experience and support commercial decisions through data analysis. The role involves creating actionable insights from customer feedback, behavior, and operational data while…
Posted 1 week ago
Customer Insight Analyst
On-siteWe’re looking for a Customer Insight Analyst to join us at Telia Norway. I’m Anna Moen , Head of Analytics , and I’m looking for a curious, business-minded analyst who is eager to learn, contribute and make an impact with us. At Telia…
Posted 3 weeks ago
Customer Insights Analyst
On-siteJoin the Canada Experience team as a Customer Insights Analyst, turning customer and employee data into actionable insights that improve experiences across Canada. You will use SQL, Power BI, AI tools, and Voice of Customer data to identify…
Posted 3 weeks ago
Product Data Analyst
On-siteProduct Data Analyst $130k – $180k • meaningful equity About Novig Novig is building America's #1 sports prediction market. Our mission is to financialize and democratize sports trading - taking a closed system run by casinos and turning it…
Posted 6 days ago
Product Data Analyst
HybridAbout Labhouse Labhouse is a fast-growing startup that builds, launches, and scales its own AI Productivity Apps under a subscription-based business model. We are based in Barcelona and were founded by Andrés Bou and Horacio Martos…
Posted 1 week ago
Data Analytics Analyst I
On-siteJoin Teleperformance as a Data Analytics Analyst I, where you'll be responsible for performing analytics and statistical modeling on various business data. Your role will involve defining data requirements, data collection, processing, cleaning,…
Posted 1 week ago
How LiftmyCV Helps with Data Analyst Jobs Search
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Learn more →Data Analytics Salary Data in October 2026
This section summarizes salary information across data analytics postings, including roles that may involve reporting, SQL, dashboards, business intelligence, and analytics support. Use it alongside the 90,752+ active postings to compare compensation patterns across current data analytics jobs.
Average Salary
$78k
$98k
$120k
25th
50th
75th
Based on 90,752 roles currently tracked by LiftmyCV. Last updated on Oct 19, 2026
Salary Distribution
Based on 90,752 roles currently tracked by LiftmyCV. Last updated on Oct 19, 2026
| Experience Level | 25th Percentile | Median (50th) | 75th Percentile | Sample Size |
|---|---|---|---|---|
| Overall | $78,448.13 | $97,500 | $120,125 | 90,752 |
| Entry-Level | $54,597 | $77,244.5 | $95,647.5 | 36 |
| Mid-Level | $77,656.2 | $92,000 | $115,006.63 | 100 |
| Senior-Level | $94,003.13 | $109,800 | $149,850 | 76 |
"For data analytics jobs in 2026, I’m seeing employers separate reporting-heavy roles from analytics roles that influence product, operations, finance, and growth decisions. SQL and dashboarding still matter, but resumes read better when they show how analysis changed a forecast, reduced manual reporting, clarified customer behavior, or improved a business workflow. The market tends to reward analysts who can explain messy data clearly, not just list tools."
Marina's Market Take
Senior HR Leader & Lead Tech Recruiter
How to Land a Data Analytics Job in 2026
Data analytics jobs usually reward candidates who can show a clear lane, not just a general interest in dashboards or data. In 2026, your application should quickly signal whether you fit business analytics, product analytics, marketing analytics, operations analytics, finance analytics, or BI reporting work. A hiring manager reviewing a data analyst, BI analyst, or analytics consultant profile wants to see the kinds of decisions your analysis supported, the datasets you worked with, and the tools you used to get from raw data to a defensible answer.
For business and operations analytics roles, emphasize SQL, Excel or Sheets, dashboard ownership, recurring reporting, and examples of improving a process, forecast, workflow, or service metric. For product analytics roles, lead with event data, funnels, retention, experimentation, cohort analysis, and comfort working with product managers or engineers. Marketing analytics candidates should point to campaign measurement, attribution, lifecycle reporting, paid media analysis, CRM data, and clear explanations of channel performance. BI-focused candidates should make reporting architecture, data visualization, stakeholder intake, and dashboard maintenance visible.
- Position your title around the role lane. Use terms like data analyst, BI analyst, product analyst, marketing analyst, or operations analyst when they match your actual work.
- Show the tools in context. SQL, Tableau, Power BI, Looker, Python, R, dbt, Snowflake, BigQuery, and Excel matter more when tied to projects, dashboards, models, or recurring decisions.
- Prioritize roles by data environment. A product analytics opening, a finance reporting role, and a customer operations analyst job may all sit under data analytics, but each needs different evidence.
- Make business outcomes readable. Describe what changed after your analysis, such as a cleaner forecast, faster reporting cycle, clearer funnel diagnosis, or better segment definition.
LiftmyCV helps you find data analytics jobs that match your skills, experience, and preferred work style, then auto-apply to relevant roles faster.
Required Skills
Resume Tips
For data analytics jobs, your resume should show how you turn raw data into decisions. Prioritize SQL, Excel, Python or R, Tableau, Power BI, Looker, dbt, BigQuery, Snowflake, and analytics work tied to reporting, dashboards, forecasting, cohort analysis, funnel analysis, or data quality. If you have certifications, keep them relevant: Google Data Analytics, Microsoft Power BI, Tableau, AWS, Snowflake, or Databricks credentials belong near your skills or education section.
Cut vague task lists, old coursework that doesn’t use data, and tool names you can’t discuss in an interview. A data analyst resume reads better when each bullet includes the business question, dataset or tool, method, and result. Use numbers where you have them, but don’t force metrics you can’t support.
- Weak: Created reports and dashboards for the business team.
- Strong: Built SQL and Power BI dashboards tracking weekly customer retention, giving sales and operations teams a clearer view of churn patterns by segment.
Entry-level candidates can use capstone projects, internships, Excel models, or public datasets, but the write-up should still explain the analysis, not just name the chart. For senior analytics roles, emphasize stakeholder work, metric definitions, experimentation, data governance, and decisions influenced by your analysis.
LiftmyCV helps you create an ATS-friendly data analytics resume tailored to each job, so your skills and experience better match what employers are looking for.
How to Prepare for Interviews
Interview preparation for data analytics jobs
Data analytics interviews usually test how you move from messy data to a defensible recommendation. Prepare examples that show SQL querying, dashboard decisions, metric definition, and how you explained findings to product, finance, operations, marketing, or leadership audiences. A useful 2026 prep set should include two or three projects where you can discuss the dataset, the business question, the metric you chose, and what changed after the analysis.
Expect more than one format. You may get a SQL screen with joins, window functions, or aggregation logic; a take-home case asking you to diagnose a drop in conversion; or a live discussion about why a dashboard metric is misleading. For analytics roles tied to growth or product, practice funnel and cohort questions. For operations analytics, prepare examples around forecasting, capacity, quality, or cost drivers. For business intelligence roles, be ready to walk through a dashboard and defend chart choices, filters, and data freshness assumptions.

