Lead AI Data Engineer
Role details
Job location
Tech stack
Job description
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:
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Build and operate production ETL/ELT pipelines processing millions of eCommerce events daily and order trends.
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Write and tune complex SQL for operational analytics, KPIs, and reporting.
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Design analytics-ready schemas and data models for performance and scale.
Requirements
Experience
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10+ years building and architecting large-scale applications and distributed systems.
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5+ years building production data pipelines, ETL/ELT workflows, and analytics platforms.
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Applied AI to operational intelligence (anomaly detection/alerting, forecasting, insights).
Core Skills (must have)
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Expert SQL (complex queries and performance tuning on large datasets).
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Spark/PySpark in production (Spark SQL, optimization).
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Strong Python (testing, packaging, modern development practices).
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ETL/ELT design: orchestration, scheduling, error handling, monitoring.
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Databricks/Delta Lake (Jobs/Workflows, Unity Catalog; Medallion patterns).
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Data modeling for analytics (dimensional models; star/snowflake schemas).
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Distributed systems fundamentals: microservices, APIs, event-driven patterns.
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Production troubleshooting and observability (logs, metrics, traces, alerting).
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AWS (S3, Lambda, Glue, Kinesis, OpenSearch, QuickSight, CloudWatch); BI (Power BI, Tableau, Grafana); LLM/GenAI (RAG, vector DBs, LangChain, Bedrock).
Application Development & System Understanding
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Distributed systems engineering (microservices, APIs, event-driven architecture, scalability patterns).
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Strong engineering discipline (design patterns, testing, code quality, Git, CI/CD) with rapid system comprehension.
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Production troubleshooting, observability (root-cause analysis; logs/metrics/traces/alerting) and AI agents for automated monitoring/notification.
Benefits & conditions
We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.
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Bonus Program
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Pension and Retirement Plans
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Medical, Dental and Vision Coverage
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Paid Time Off
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Paid Parental Leave