Senior Data Analyst Resume Example
Hiring managers evaluating Senior Data Analysts look for end-to-end architecture ownership measured by business impact, not dashboard delivery without strategic context.
This resume is for senior data analysts who lead high-impact technical projects and mentor junior team members, but aren't yet responsible for departmental headcount or multi-year data roadmaps.
- Ownership of end-to-end data architecture and modeling workflows
- Evidence of driving measurable business outcomes through statistical experimentation
- Demonstrated ability to mentor peers and standardize data practices across teams
- Professional summary emphasizing technical scope and leadership
- Skills section grouped by analytical tools and strategic domains
- Experience entries prioritizing high-level business outcomes over task lists
Imani Wright
Summary
Experience
- Engineered a suite of dbt models to centralize supply chain data, reducing dashboard latency by 48% across the operations department.
- Optimized warehouse replenishment logic using Python, resulting in a $340K reduction in annual carrying costs for the Northeast region.
- Mentored 3 junior analysts on SQL optimization and data storytelling, increasing the team's weekly report throughput by 32%.
- Directed the migration of legacy Excel-based reporting to Looker for the logistics team, serving 150+ internal stakeholders with real-time delivery metrics.
- Designed and implemented an automated fraud detection dashboard in Tableau, identifying $240K in suspicious transaction patterns within the first quarter of deployment.
- Executed 22 A/B tests on the user onboarding flow, improving the verification completion rate from 64% to 78% for new retail accounts.
- Spearheaded a cross-functional data audit with 5 engineering teams to standardize event logging for 1.2M monthly active users, improving data integrity for product analytics.
- Developed SQL-based churn prediction models to identify at-risk enterprise accounts, enabling the sales team to recover $215K in potential lost revenue.
- Streamlined the monthly financial reporting process using Python and the GitLab API, saving the accounting team 15 hours of manual data entry per month.
Education
Skills
SQL · Python · R · Tableau · Looker · Snowflake · BigQuery · dbt · Statistical Modeling · A/B Testing · Experimentation · Data Strategy · Excel · Git · Data Visualization
What makes this resume effective
- This resume meets the hiring bar for a senior data analyst by demonstrating ownership of data modeling, measurable revenue impact through experimentation, and formal mentorship of junior staff.
- Notice how Imani’s work at Chewy involved engineering dbt models to centralize supply chain data, which shows technical architecture skills beyond simple dashboarding.
- See how the Coinbase experience highlights leading a cross-functional data audit with 5 engineering teams to standardize event logging for 1.2M users, proving senior-level influence.
How to write better bullet points
Built a dashboard for the logistics team to track deliveries.
Directed the migration of legacy reporting to Looker for the logistics team, serving 150+ internal stakeholders with real-time delivery metrics.
It replaces a passive task with active leadership and defines the scale of the impact across the organization.
Mentored junior analysts on the team.
Mentored 3 junior analysts on SQL optimization and data storytelling, increasing the team's weekly report throughput by 32%.
It quantifies the mentorship and links it to a tangible improvement in team productivity.
Used Python to improve warehouse replenishment.
Optimized warehouse replenishment logic using Python, resulting in a $340K reduction in annual carrying costs for the Northeast region.
It connects a technical skill directly to a high-dollar business outcome that hiring managers value.
Senior Data Analyst resume writing tips
- Highlight where you’ve standardized processes, like Imani’s dbt centralization, to show technical leadership and ownership.
- Quantify the business value of your insights, such as the $340K cost reduction at Chewy or the $240K fraud identification at Coinbase.
- Include specific mentorship outcomes to prove you can scale your impact through others without a formal manager title.
Common mistakes
- Listing only technical tasks without business outcomes. At this level, you must show how your analysis changed a decision or saved money.
- Failing to mention cross-functional collaboration. Senior roles require working with engineering or product teams to ensure data integrity and adoption.
- Neglecting to show technical leadership. Don't just build dashboards; explain how you improved the underlying data infrastructure or team workflows.
Frequently asked questions
Is this resume right for someone with 5 years of experience? Yes, if your work has shifted from ticket execution to leading projects and mentoring others rather than just fulfilling data requests.
Yes, if your work has shifted from ticket execution to leading projects and mentoring others rather than just fulfilling data requests.
Yes, if you have moved beyond executing requests and are now leading projects or mentoring others. If your experience is still focused primarily on task-based tickets without strategic input, you may want a mid-level example.
What if I haven't worked at large tech companies like Coinbase or Chewy? Yes, focus on the complexity of the problems solved and the scale of your business impact rather than the company's brand name or size.
Yes, focus on the complexity of the problems solved and the scale of your business impact rather than the company's brand name or size.
The principles of this resume apply to any industry where data drives decisions. Focus on the scale of your impact and the complexity of the problems you solved rather than the brand name of the employer.
What if I don't have exact dollar amounts for my impact? Use percentage improvements or efficiency gains to quantify the value of your insights when financial data is unavailable.
Use percentage improvements or efficiency gains to quantify the value of your insights when financial data is unavailable.
You can use percentages or efficiency gains if financial data isn't available. In this resume, Imani uses a mix of dollar amounts and percentage improvements in latency or throughput to prove value.
How much should I change before applying? Maintain the action-context-result bullet structure while updating the tech stack and business domains to match the specific job description.
Maintain the action-context-result bullet structure while updating the tech stack and business domains to match the specific job description.
You should keep the structure of the bullets—action, context, and result—but update the specific technologies and business domains. Ensure the skills section reflects the specific stack mentioned in the job description you are targeting.
What do hiring managers focus on at this level? They prioritize force multipliers who influence stakeholders and improve team infrastructure through cleaner data, better tools, or mentorship.
They prioritize force multipliers who influence stakeholders and improve team infrastructure through cleaner data, better tools, or mentorship.
They are looking for force multipliers who improve the whole team through better tools, cleaner data, or mentorship. They prioritize candidates who show they can work independently and influence stakeholders across the company.
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