McAfee
Lead AI Data Engineer - Frisco
Salary
-
Job type
Full-time
Location
Frisco, Texas, US
Remote
No
Posted
1 week ago
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Role Overview
Join our eCommerce Operational Intelligence team as a hands-on Lead AI Data Engineer. You will build enterprise-scale data pipelines and analytics foundations (SQL, Spark/PySpark, ETL/ELT) that produce reliable operational insights and measurable business impact.
The Lead AI Data Engineer will drive the transformation of eCommerce operational analytics and real-time monitoring by building scalable data pipelines, AI-powered insights, and intelligent dashboards. This role leads AI proof-of-concepts and contributes to production-grade solutions that improve platform reliability, accelerate root-cause identification, enhance engineering productivity, and strengthen operational intelligence across McAfee’s eCommerce ecosystem.
This is a Hybrid position located in Frisco, TX. You will be required to be on-site on an as-needed basis; when you are not working on-site, you will work from your home office. You must be within commutable distance of Frisco, TX. We are not offering relocation assistance at this time.
About the Role
- Build and operate production ETL/ELT pipelines processing millions of eCommerce events daily and order trends.
- Write and tune complex SQL for operational analytics, KPIs, and reporting.
- Design analytics-ready schemas and data models for performance and scale.
- Troubleshoot pipelines, microservices, and APIs; apply observability to isolate root causes.
- Integrate data across eCommerce, MarTech, and operational systems into unified insights.
- Build AI-driven anomaly detection/notification.
About You
Experience
- 10+ years building and architecting large-scale applications and distributed systems.
- 5+ years building production data pipelines, ETL/ELT workflows, and analytics platforms.
- Applied AI to operational intelligence (anomaly detection/alerting, forecasting, insights).
Core Skills (must have)
- Expert SQL (complex queries and performance tuning on large datasets).
- Spark/PySpark in production (Spark SQL, optimization).
- Strong Python (testing, packaging, modern development practices).
- ETL/ELT design: orchestration, scheduling, error handling, monitoring.
- Databricks/Delta Lake (Jobs/Workflows, Unity Catalog; Medallion patterns).
- Data modeling for analytics (dimensional models; star/snowflake schemas).
- Distributed systems fundamentals: microservices, APIs, event-driven patterns.
- Production troubleshooting and observability (logs, metrics, traces, alerting).
- AWS (S3, Lambda, Glue, Kinesis, OpenSearch, QuickSight, CloudWatch); BI (Power BI, Tableau, Grafana); LLM/GenAI (RAG, vector DBs, LangChain, Bedrock).
Application Development & System Understanding
- Distributed systems engineering (microservices, APIs, event-driven architecture, scalability patterns).
- Strong engineering discipline (design patterns, testing, code quality, Git, CI/CD) with rapid system comprehension.
- Production troubleshooting, observability (root-cause analysis; logs/metrics/traces/alerting) and AI agents for automated monitoring/notification.
#LI-Hybrid
Company Overview
McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users’ needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.
Company Benefits and Perks
We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We’re proud to be Great Place to Work® Certified in 10 countries, a reflection of the supportive, empowering environment we’ve built where people feel seen, valued, and energized to reach their full potential and thrive.
We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.
- Bonus Program
- Pension and Retirement Plans
- Medical, Dental and Vision Coverage
- Paid Time Off
- Paid Parental Leave
- Support for Community Involvement
We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.
Responsibilities
- Join our eCommerce Operational Intelligence team as a hands-on Lead AI Data Engineer
- You will build enterprise-scale data pipelines and analytics foundations (SQL, Spark/PySpark, ETL/ELT) that produce reliable operational insights and measurable business impact
- The Lead AI Data Engineer will drive the transformation of eCommerce operational analytics and real-time monitoring by building scalable data pipelines, AI-powered insights, and intelligent dashboards
- This role leads AI proof-of-concepts and contributes to production-grade solutions that improve platform reliability, accelerate root-cause identification, enhance engineering productivity, and strengthen operational intelligence across McAfee’s eCommerce ecosystem
- Build and operate production ETL/ELT pipelines processing millions of eCommerce events daily and order trends
- Write and tune complex SQL for operational analytics, KPIs, and reporting
- Design analytics-ready schemas and data models for performance and scale
- Troubleshoot pipelines, microservices, and APIs; apply observability to isolate root causes
- Integrate data across eCommerce, MarTech, and operational systems into unified insights
- Build AI-driven anomaly detection/notification
- ETL/ELT design: orchestration, scheduling, error handling, monitoring
- Databricks/Delta Lake (Jobs/Workflows, Unity Catalog; Medallion patterns)
- Distributed systems fundamentals: microservices, APIs, event-driven patterns
- Production troubleshooting and observability (logs, metrics, traces, alerting)
- Distributed systems engineering (microservices, APIs, event-driven architecture, scalability patterns)
- Production troubleshooting, observability (root-cause analysis; logs/metrics/traces/alerting) and AI agents for automated monitoring/notification
Qualifications
- 10+ years building and architecting large-scale applications and distributed systems
- 5+ years building production data pipelines, ETL/ELT workflows, and analytics platforms
- Applied AI to operational intelligence (anomaly detection/alerting, forecasting, insights)
- Expert SQL (complex queries and performance tuning on large datasets)
- Spark/PySpark in production (Spark SQL, optimization)
- Strong Python (testing, packaging, modern development practices)
- Data modeling for analytics (dimensional models; star/snowflake schemas)
- AWS (S3, Lambda, Glue, Kinesis, OpenSearch, QuickSight, CloudWatch); BI (Power BI, Tableau, Grafana); LLM/GenAI (RAG, vector DBs, LangChain, Bedrock)
- Application Development & System Understanding
- Strong engineering discipline (design patterns, testing, code quality, Git, CI/CD) with rapid system comprehension
Benefits
- We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees
- Bonus Program
- Pension and Retirement Plans
- Medical, Dental and Vision Coverage
- Paid Time Off
- Paid Parental Leave
- Support for Community Involvement
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