Full-Time

Senior Information Security Engineer

Posted on 9/11/2025

Mixpanel

Mixpanel

501-1,000 employees

SaaS analytics platform tracking user behavior

Compensation Overview

$216k - $264k/yr

+ TTCC + Equity consideration + other benefits including medical, vision, and dental insurance coverage

San Francisco, CA, USA

Hybrid

Category
IT & Security (4)
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Requirements
  • A track record of 5+ years of experience as a security engineer, with a focus on defining and driving security initiatives within an engineering-centric organization.
  • A proven ability to provide technical leadership and mentor other engineers, acting as a force multiplier for the team and beyond.
  • Extensive experience with the secure software development lifecycle, including a deep understanding of security best practices, and a history of advocating for them with engineering and product teams.
  • The ability to translate strategic ideas into mature projects, leveraging scripting, automation, and a variety of GenAI platforms (e.g., Gemini, ChatGPT, Claude) to build innovative solutions.
  • A deep knowledge of the Product Security domain, with a strong generalist background and hands-on experience in other core security areas.
  • A history of driving security outcomes by collaborating effectively with engineering, product, and senior leadership.
Responsibilities
  • Define and own the Product Security strategy, working hand-in-hand with engineering teams to orchestrate security testing of new features and lead the triage and mitigation of vulnerabilities from tools like HackerOne, Detectify, and GitHub Advanced Security.
  • Serve as a security Subject Matter Expert (SME), providing consultation and guidance to internal teams and directly with customers to ensure business solutions are secure.
  • Proactively anticipate emerging security requirements and recommend new policies, procedures, and controls that address potential threats and maintain our security posture.
  • Develop and lead secure software development training to enable Product and Engineering teams to improve their security practices.
  • Work directly with senior leadership to report on domain performance, communicate security metrics, and manage project planning and execution.
Desired Qualifications
  • Experience with designing and implementing next-generation security technologies, such as SASE, CASB, or RASP.
  • Hands-on experience with application patch management, software supply chain security, or artifact repositories like JFrog and Snyk.
  • A background working at a SaaS company, with extensive experience in data analytics and the Google enterprise security stack (GCP and Google Workspace).
  • Experience with multiple-control frameworks, including SOC 2 Type 2, ISO 27001, and ISO 27701.
  • Relevant professional certifications (e.g., CISSP, CCSP, OSCP) or an advanced degree in a related technical field.

Mixpanel is a data analytics platform that helps businesses understand how users interact with their products. It operates as a Software-as-a-Service (SaaS) with tools to track user behavior across websites and mobile apps, using features like event tracking, user segmentation, funnel analysis, and retention reports. Customers subscribe to different pricing tiers based on data volume and available features, and Mixpanel generates revenue from analytics access, as well as premium support and consulting services. Its goal is to help companies optimize user experience and grow by enabling data-driven decisions.

Company Size

501-1,000

Company Stage

Series C

Total Funding

$277.2M

Headquarters

San Francisco, California

Founded

2009

Simplify Jobs

Simplify's Take

What believers are saying

  • Jen Taylor, ex-Cloudflare CPO, appointed CEO in September 2025 to drive expansion.
  • Mixpanel AI rolls out to all 29,000 customers by June 2026 via Claude and Slack integrations.
  • Fleece AI automates Mixpanel workflows, boosting adoption among product teams since March 2026.

What critics are saying

  • Fleece AI commoditizes Mixpanel data, automating alerts across 3,000 apps in 6-12 months.
  • PostHog undercuts pricing with unlimited open-source event tracking, capturing startups in 3-6 months.
  • Amplitude erodes share with AI anomaly detection and session replay in 12-18 months.

What makes Mixpanel unique

  • Mixpanel AI proactively surfaces insights using specialized agents for onboarding and KPI monitoring.
  • Metric Trees connect KPIs to business impact with AI-assisted hierarchies on Enterprise Plan.
  • Acquisition of DoubleLoop advances AI-driven product-to-revenue frameworks in 2026.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Competitive compensation

Company stock options

Sabbatical policy

PTO

Volunteer time off

Parental leave

Mental health resources

401(k) match

Health, dental,& vision coverage

Flexible work from home options

Learning & development stipend

Professional growth hours

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-2%

2 year growth

-4%
Hi-Tech Weirdo
Mar 21st, 2026
Software tools that companies often switch to from Amplitude analytics platforms.

Software tools that companies often switch to from Amplitude analytics platforms. March 21, 2026 Blog As businesses mature in their digital analytics journey, many begin exploring alternatives to their current analytics stack. While Amplitude is widely recognized for its robust product analytics capabilities, organizations often reassess their needs due to pricing, integration complexity, scalability concerns, or evolving business objectives. As a result, companies frequently transition to other analytics or business intelligence platforms that align better with their data strategy, internal expertise, or budget considerations. TLDR: Companies switch from Amplitude to other analytics tools for reasons such as cost efficiency, broader business intelligence capabilities, easier integrations, or more advanced customization. Popular alternatives include Mixpanel, Google Analytics 4, Heap, Adobe Analytics, Tableau, Looker, and Segment. Each platform offers different strengths in areas like event tracking, visualization, enterprise reporting, or data warehousing. The right choice depends on a company's size, goals, and data maturity. Why companies move away from Amplitude. Table of Contents Although Amplitude is powerful for product analytics and behavioral tracking, businesses may outgrow it or find it misaligned with their expanding needs. Common reasons include: * Pricing concerns: Scaling event-based analytics can become costly. * Broader BI needs: Some companies require full business intelligence, not just product metrics. * Data ownership: Preference for warehouse-native analytics. * Complex integrations: Teams may desire easier syncing with CRM, marketing, or finance systems. * Customization and flexibility: Advanced queries or data modeling may demand different infrastructure. This shift does not necessarily indicate dissatisfaction. Instead, it reflects an evolution in data sophistication and organizational priorities. Common alternatives companies choose. 1. Mixpanel. Mixpanel is one of the most direct competitors to Amplitude. It specializes in product analytics, offering advanced event tracking, funnels, retention analysis, and cohort reporting. Why companies switch: * User-friendly interface * Strong behavioral analytics * Transparent pricing tiers * Quick implementation for startups Organizations seeking similar functionality but improved usability or pricing predictability often consider Mixpanel a seamless alternative. 2. Google Analytics 4 (GA4). Google Analytics 4 provides event-based tracking while integrating deeply with Google Ads and other marketing tools. Reasons for switching: * Free core version * Marketing attribution features * Cross-platform tracking * Strong advertising ecosystem integration Companies heavily invested in digital marketing often migrate to GA4 to centralize analytics with advertising data. 3. Heap. Heap differentiates itself with automatic event tracking. Instead of manually defining events, Heap captures everything, allowing retroactive analysis. Appeal factors: * No-code event tracking * Reduced engineering dependency * Faster experimentation cycles For teams with limited technical resources, Heap can significantly reduce setup complexity. 4. Adobe Analytics. Enterprise organizations frequently move toward Adobe Analytics for its depth and customization. Advantages: * Advanced segmentation * AI-powered insights * Integration with Adobe Experience Cloud * Highly scalable infrastructure Large corporations with complex customer journeys and cross-channel marketing strategies often find Adobe Analytics more suitable. 5. Tableau. Tableau is not a direct product analytics tool but a powerful business intelligence platform. Companies sometimes switch from Amplitude to Tableau when they require broader reporting capabilities beyond user behavior. * Rich data visualization * Custom dashboards * Data blending from multiple sources * Enterprise reporting It excels in executive-level dashboards and organization-wide performance tracking. 6. Looker (Google Cloud). Looker is a warehouse-native business intelligence tool built for custom modeling and scalable analytics. Why companies choose Looker: * Advanced data modeling with LookML * Direct warehouse connection * Governed data access * Scalable enterprise reporting Organizations emphasizing centralized data governance often adopt Looker. 7. Segment. Segment is primarily a Customer Data Platform (CDP), but many companies migrate toward it when they prioritize unified data pipelines over standalone analytics. * Centralized data collection * Integration with 300+ tools * Improved data flow management Rather than replacing analytics entirely, Segment often becomes the foundation powering new analytics systems. Comparison chart of popular alternatives. | Tool | Primary Focus | Best For | Pricing Level | Technical Complexity | | Mixpanel | Product Analytics | Startups & SaaS | Moderate | Medium | | Google Analytics 4 | Marketing & Web Analytics | Marketing Teams | Low (Free Tier) | Low-Medium | | Heap | Automatic Event Tracking | Lean Product Teams | Moderate-High | Low | | Adobe Analytics | Enterprise Analytics | Large Enterprises | High | High | | Tableau | Business Intelligence | Executives & BI Teams | Moderate-High | Medium | | Looker | Warehouse-Native BI | Data-Driven Organizations | High | High | | Segment | Customer Data Platform | Multi-Tool Ecosystems | Moderate-High | Medium | Key considerations before switching. Switching analytics platforms can significantly impact workflows, data consistency, and decision-making processes. Companies typically evaluate the following factors: 1. Data migration complexity. Historical data export and reconfiguration of tracking events require careful planning. Improper migration can result in broken dashboards or incomplete reports. 2. Engineering resources. Some tools require heavy implementation effort, particularly warehouse-native or enterprise systems. Organizations assess internal technical capacity before committing. 3. Scalability. Fast-growing companies prioritize systems that scale alongside event volume and user growth without unsustainable pricing. 4. Integration ecosystem. Compatibility with CRMs, marketing platforms, customer support tools, and data warehouses is essential for unified analytics strategies. 5. Cost efficiency. Event-based pricing models can become unpredictable. Companies often analyze total cost of ownership over three to five years before switching. Emerging trend: warehouse-native analytics. An increasingly common shift involves moving away from standalone SaaS analytics platforms toward warehouse-native solutions. Tools such as Looker, Mode, and even open-source frameworks allow organizations to leverage Snowflake, BigQuery, or Redshift directly. This approach offers: * Greater data ownership * Enhanced security control * Reduced duplicate data storage * Improved cross-department reporting For businesses embracing modern data stacks, this model can be more cost-effective long term. Conclusion. Amplitude remains a leader in product analytics, but it is not a one-size-fits-all solution. As companies mature, diversify, or refine their analytics goals, many transition to platforms that better support enterprise intelligence, marketing attribution, warehouse-native workflows, or cost predictability. The decision to switch depends less on dissatisfaction and more on alignment - between platform capabilities and strategic objectives. Whether migrating to Mixpanel for streamlined product insights, GA4 for marketing synergy, Tableau for executive dashboards, or Looker for governed data scalability, companies aim to build analytics ecosystems that empower long-term growth. Frequently asked questions (FAQ). 1. Why do companies switch from Amplitude? Companies typically switch due to pricing concerns, broader business intelligence requirements, integration needs, or a desire for warehouse-native analytics. 2. Is Mixpanel better than Amplitude? Neither platform is universally better. Mixpanel may offer simpler pricing and usability advantages, while Amplitude provides strong experimentation and advanced analytics features. 3. What is the most cost-effective alternative? Google Analytics 4 offers a robust free tier, making it attractive for budget-conscious organizations, though it may lack some advanced product analytics features. 4. Are enterprise companies more likely to switch to Adobe Analytics? Yes, large enterprises often move to Adobe Analytics due to its scalability, customization options, and integration with the Adobe Experience Cloud ecosystem. 5. What is warehouse-native analytics? Warehouse-native analytics connects directly to a company's data warehouse, minimizing duplication and enhancing governance while allowing powerful custom reporting. 6. Is switching analytics platforms risky? Switching requires careful planning, particularly regarding data migration and retraining teams. However, with proper implementation, it can significantly improve decision-making efficiency.

Fleece AI
Mar 13th, 2026
Automate Mixpanel with AI Agents (2026)

Automate Mixpanel with AI agents (2026). By Loïc Jané · Founder, Fleece AI How to automate Mixpanel with AI agents. At a Glance: Fleece AI connects to Mixpanel and lets autonomous agents monitor funnels, track user behavior, generate reports, and trigger data-driven workflows across 3,000+ apps. Updated March 2026. Mixpanel is the product analytics platform trusted by over 9,000 companies including Uber, Yelp, and DocuSign. Mixpanel tracks user events, analyzes funnels, measures retention, and enables cohort analysis - giving product teams the data to make informed decisions. But turning analytics data into action still requires manual work: exporting reports, sharing insights across teams, and triggering responses to user behavior. Product teams check dashboards, export CSVs, copy insights into presentations, and manually alert stakeholders when metrics shift. According to McKinsey, companies that systematically act on analytics data outperform peers by 23% in revenue growth - yet most teams struggle to operationalize their analytics beyond periodic manual reviews. Fleece AI connects to Mixpanel (and 3,000+ other apps) to automate analytics-driven workflows with autonomous AI agents. Turn your Mixpanel data into automated actions without writing code. What Mixpanel automation looks like with AI. Mixpanel dashboards show you what happened. AI-native automation acts on what the data reveals: 1. Funnel drop-off alerts. "Every morning at 8 AM, query our Mixpanel signup funnel for the past 24 hours. If the conversion rate from 'Started Signup' to 'Completed Signup' drops below 60%, alert the product team on Slack with the current conversion rate, the step with the highest drop-off, and a comparison to the 7-day average." 2. Feature adoption tracking. "Every Monday, query Mixpanel for the number of unique users who used our new 'Export' feature last week. Compare to the prior week. Post a feature adoption report to Slack #product with the trend, total adopters since launch, and percentage of monthly active users. Log the data in Google Sheets." 3. User behavior-triggered outreach. "Every hour, query Mixpanel for users who completed their 3rd project in the past 60 minutes (power user signal). Add them to our 'Power Users' segment in HubSpot and trigger a personalized congratulations email via Gmail with an upsell offer for the Pro plan." 4. Retention cohort monitoring. "On the 1st of every month, pull 30-day retention data from Mixpanel for the prior month's signup cohort. Compare against the 3-month rolling average. If retention dropped by more than 5 percentage points, create a Linear investigation ticket and notify the PM on Slack." How it works. * Connect Mixpanel - Fleece AI authenticates via Pipedream using your Mixpanel service account credentials. * Describe your workflow - Write what you want in plain English. The agent queries the right Mixpanel endpoints. * Set a schedule - Choose a cron frequency with timezone support. * Agent executes - The AI agent queries analytics data, identifies trends, and coordinates across connected apps. * Review results - Check execution logs in your Fleece AI dashboard. Cross-App workflows with Mixpanel. | Workflow | Apps Involved | | Funnel drop-off alerts | Mixpanel -> Slack | | Feature adoption to spreadsheet | Mixpanel -> Google Sheets | | Power user identification | Mixpanel -> HubSpot | | Retention alerts to PM | Mixpanel -> Linear | | Churn risk to CRM | Mixpanel -> Salesforce | | Usage data to onboarding flow | Mixpanel -> Intercom | Popular Mixpanel automations. For Product Managers: * Daily funnel performance monitoring with anomaly detection * Feature launch adoption tracking across cohorts * Retention trend analysis with automated investigation triggers For Growth Teams: * Power user identification and CRM enrichment * Trial-to-paid conversion rate monitoring * Churn risk scoring based on usage patterns For Engineering: * Performance metric tracking post-deployment * Error event correlation with user experience data * A/B test metric monitoring with statistical significance alerts Mixpanel automation vs manual analytics. | Capability | Manual Analysis | Fleece AI + Mixpanel | | Funnel monitoring | Check dashboards periodically | Agent alerts on anomalies | | Feature tracking | Monthly review meetings | Weekly automated reports | | User segmentation | Export and analyze CSVs | Auto-tag in CRM in real-time | | Retention analysis | Quarterly deep dives | Monthly automated cohort reports | | Insight distribution | Screenshots in Slack | Formatted digests on schedule | Turn analytics into action. Start free on Fleece AI - connect Mixpanel in 60 seconds. Frequently asked questions. Can Fleece AI query Mixpanel events and funnels? Yes. Fleece AI agents can query Mixpanel's Query API to retrieve event data, funnel metrics, retention tables, and cohort analyses. The agent handles the JQL or query parameter construction based on your natural language description - no need to write Mixpanel queries manually. Can Fleece AI export Mixpanel data to other tools? Yes. The agent can pull data from Mixpanel and push it to Google Sheets, Airtable, Notion, or any connected app. This enables automated reporting pipelines that keep stakeholders informed without manual CSV exports. Do I need a paid Mixpanel plan? Mixpanel's free plan includes up to 20M monthly events and full API access. Fleece AI connects through the standard Mixpanel API, so the free tier works for most automation use cases. Advanced features like group analytics require Mixpanel's Growth or Enterprise plans. How is this different from Mixpanel's built-in alerts? Mixpanel's custom alerts notify you when a metric crosses a threshold. Fleece AI agents act on the data: when a funnel drops, the agent does not just send a Slack message - it can create an investigation ticket in Linear, tag affected users in HubSpot, and compile a comparative analysis, all autonomously. Can Fleece AI send events to Mixpanel? Yes. The agent can send custom events to Mixpanel via the Ingestion API. This enables automated event tracking from external sources - for example, logging support ticket resolution events from Zendesk as Mixpanel events for customer experience analysis. * Automate Google Sheets with AI - spreadsheet automation * Automate HubSpot with AI - CRM automation * Automate Linear with AI - engineering project automation * Automate Slack with AI - team communication automation * Automate Intercom with AI - customer messaging automation * Automate Sentry with AI - error tracking automation Try Fleece AI free - deploy your first Mixpanel analytics automation in under 60 seconds. Ready to delegate your first task? Deploy your first AI agent in under 60 seconds. No credit card required.

Legal Tech Monitor
Dec 3rd, 2025
OpenAI, Mixpanel Hit With Novel Data Breach Class Action Over November Cyberattack

OpenAI, Mixpanel hit with novel data breach class action over November cyberattack. ChatGPT maker OpenAI and third-party web analytics platform Mixpanel were both hit with a data breach class action on Monday over their alleged failure to protect users' personally identifiable information from a November cyberattack.

IBT Media
Nov 27th, 2025
OpenAI Confirms Mixpanel Breach Exposed Names, Emails Of Some API Users - Act Now

OpenAI confirms Mixpanel breach exposed names, emails of some API users - act now. OpenAI has confirmed a data breach involving its third-party analytics tool, Mixpanel, that exposed names and email addresses for a portion of its API users. Because this sensitive information is vulnerable to phishing attacks, all affected users must take immediate steps to secure their accounts. The security event stemmed from a compromise of Mixpanel's systems, not a failure within OpenAI's own infrastructure. This breach allowed an attacker to access and copy a data file containing a small amount of identifying information for certain OpenAI API customers. Crucial alert: openai confirms Mixpanel data exposure. Mixpanel initially noticed suspicious activity within a section of its systems. An intruder then managed to extract a file containing customer details alongside their usage data. Mixpanel promptly alerted OpenAI, which was using the service exclusively for web tracking on the front end of its API product at platform.openai.com. The AI company, led by Sam Altman, stated in a blog post that the security issue had no impact on users of ChatGPT or any of its other offerings. Crucially, this did not affect OpenAI's main infrastructure; information such as chat history, API requests, usage statistics, passwords, sign-in details, API keys, payment records, or official identification remains secure. Mixpanel provided the compromised data to OpenAI on 25 November 2025, enabling OpenAI to begin its own review and contact affected individuals. Details of compromised information. The data file retrieved from Mixpanel's system contained limited account details and platform-specific usage statistics for the openai.com interface. * The name provided for the API account. * The email address connected to the API account. * Rough geographical position inferred from the user's web browser (including city, county, and country). * The operating system and browser employed when accessing the API account. * Websites that directed the user to the platform. * The unique identifiers (IDs) linked to the organisation or the user's API account. OpenAI's immediate action. OpenAI responded swiftly to handle the data exposure. After completing the security assessment, the company promptly disconnected Mixpanel from its active production services. Mixpanel CEO Jen Taylor explained that the company identified a 'smishing' attack and immediately launched its emergency response procedures. 'We took comprehensive steps to contain and eradicate unauthorised access and secure impacted user accounts. We engaged external cybersecurity partners to remediate and respond to the incident,' the top executive confirmed in a blog post. Despite these efforts, OpenAI confirmed it has stopped using Mixpanel. The focus now is on directly informing all affected groups, including organisations, administrators, and individual users, through email. OpenAI stated that although no evidence of data misuse has been found, it is still actively monitoring for any signs of related malicious activity. In addition, the company announced that it is undertaking broader, more thorough security checks across its entire network of suppliers and increasing security standards for all external partners. Key actionable steps for API users. The exposed details, which include your name, email address, and account metadata, could be used by criminals in phishing or social engineering attempts targeting you or your organisation. OpenAI is urging all API users to stay alert for any suspicious communication. This involves treating any unexpected emails or messages with extreme care, particularly those that include links or attachments. Users must always confirm that any message claiming to be from OpenAI actually originates from an official company domain. It is crucial to remember that OpenAI will never ask for sensitive information such as passwords, API keys, or verification codes via email, text, or chat. Lastly, although no passwords were leaked in this event, activating Multi-Factor Authentication (MFA) is still essential for protecting accounts from unwanted access; organisations should implement MFA through their single sign-on system. No need to reset. OpenAI is not advising users to change their passwords or generate new API keys since those elements were not compromised in the breach. If users have any further concerns, OpenAI encourages them to contact its support team.

HackRead
Nov 27th, 2025
OpenAI API User Data Exposed in Mixpanel Breach, ChatGPT Unaffected

OpenAI API user data exposed in Mixpanel breach, ChatGPT unaffected. OpenAI confirmed a third-party data breach via Mixpanel, exposing limited API user metadata like names, emails and browser info. OpenAI systems were not breached, and no passwords, API keys, chats or payment data were exposed. OpenAI has confirmed a data breach involving Mixpanel, a third-party analytics tool it used to monitor API dashboard activity. This wasn't a direct attack on OpenAI's systems but a compromise of Mixpanel, where an attacker accessed and exported data linked to API users. To be specific, this wasn't about passwords, payment info or anything that gives direct access. What got taken was account metadata, the kind of stuff analytics tools collect by default, including: * Name * Email address * Referring website * City, state or country * Internal user or org ID * Browser and operating system OpenAI responded by immediately removing Mixpanel from its production systems and launched a review to identify what was affected. It has since notified all impacted users. The company is also conducting a broader audit of its external vendors and has advised users to turn on multi-factor authentication and be cautious with unsolicited messages or phishing attempts. It's worth clarifying that regular ChatGPT users weren't affected. The exposure was limited to those who interacted with OpenAI through its API platform. Mixpanel confirmed that it had detected suspicious access on one of its service environments and that the attacker had exported data belonging to multiple customers, including OpenAI. The company says it has since resolved the vulnerability and engaged external security experts to investigate. This kind of third-party breach is far from rare. Many companies rely on analytics providers, payment processors, and support platforms, each of which brings a certain level of risk. While no system is bulletproof, what matters is how companies react once something breaks. In this case, OpenAI took its vendor offline, dug through the damage, and notified those affected without delay. Ben Schilz, CEO of Wire, weighed in on the incident with a broader perspective, stating that the real issue isn't just the breach itself, but the growing reliance on third-party tools that companies don't fully control. He pointed to the need for "digital sovereignty," stressing that organisations need to stay in charge of their own data and security rather than handing over that control to external vendors. Data breach monitoring The good news is that ChatGPT user data wasn't affected, and OpenAI has already cut off the third-party vendor involved. The downside is that some data was stolen, and there's a real chance it could be leaked or used in phishing attempts targeting those same users. Therefore, be cautious with any emails claiming to be from OpenAI or Mixpanel, especially ones asking you to reset passwords or review security settings. It's also a good time to enable two-factor authentication on both your OpenAI account and the email linked to it. I am a UK-based cybersecurity journalist with a passion for covering the latest happenings in cybersecurity and tech world. I am also into gaming, reading and investigative journalism.

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