Lead AI Data Engineer - Frisco

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. Company Benefits and Perks Bonus Program Pension and Retirement Plans Medical, Dental and Vision Coverage Paid Time Off Paid Parental Leave Support for Community Involvement We prohibit 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. #J-18808-Ljbffr McAfee