Sr. Data Engineer

Role Summary

We are looking for a Sr Data Engineer for our Consumer Protection Team to transform operational analytics for the consumer protection team to analyze customer and internal data, improving both what our products deliver and how they are delivered. Drive efficiency of the CP organization and enhance effectiveness and reliability of CP products through scalable data pipelines, AI-powered insights, and real-time monitoring.

This is a Hybrid position located at our Frisco, USA. You will be required to be on-site 2 to 3 days per week. When you are not working on-site, you will be working from your home office. We are only considering candidates within a commutable distance to our Frisco office and are not offering relocation assistance at this time.

Position Details

About the Role

• Design, build, and maintain scalable data platforms, pipelines, and services that support analytics, machine learning, and AI-powered applications.

• Architect and optimize batch and real-time data processing solutions across cloud-native environments, including AWS and GCP.

• Analyze large-scale product, customer, and operational datasets to identify trends, patterns, anomalies, and opportunities that translate into meaningful product and engineering insights.

• Turn data into actionable recommendations that improve product experience, customer satisfaction, engagement, performance, reliability, and business outcomes.

• Partner with Product, Engineering, Data Science, and UX teams to define meaningful metrics, investigate customer behavior and friction points, and influence product priorities using data.

• Leverage AI/ML and advanced analytics to uncover insights at scale, identify emerging patterns, predict potential issues, and accelerate root-cause analysis

• Develop high-performance data APIs, microservices, and integrations using Python, Golang, and modern containerized architectures.

• Lead the design and implementation of distributed data systems utilizing technologies such as Spark, Hadoop, Kafka, DynamoDB, MongoDB, Cassandra, and S3.

• Build and maintain reliable data ingestion, transformation, and orchestration frameworks that enable trusted, high-quality data across the organization.

• Design and implement streaming and event-driven architectures using technologies such as Kafka, Redis, and RabbitMQ.

• Develop and optimize data solutions supporting LLM-based applications, retrieval-augmented generation (RAG), vector search, and AI model workflows.

• Establish engineering standards for data quality, observability, governance, performance, reliability, and security.

• Lead technical design discussions, conduct architecture reviews, and influence data engineering best practices across multiple teams and initiatives.

• Mentor engineers and provide technical leadership on complex cross-functional projects.

About You

• 10+ years of software and data engineering experience, including significant experience building large-scale cloud-based data platforms.

• Strong analytical mindset with demonstrated ability to move beyond data processing and derive meaningful insights from complex datasets.

• Experience translating telemetry, behavioral, operational, and product data into actionable recommendations for Product and Engineering teams.

• Ability to connect technical data signals with customer experience and business outcomes, and communicate those insights effectively to technical and non-technical stakeholders.

• Strong programming experience with Python and Golang, including building distributed systems, APIs, and cloud-native applications.

• Deep expertise in SQL, NoSQL, and large-scale data processing technologies including DynamoDB, MS SQL, Cassandra, MongoDB, Apache Spark, Hadoop, and S3.

• Hands-on experience designing and supporting real-time data processing and event-driven architectures using Kafka, Redis, RabbitMQ, or similar technologies.

• Experience designing and optimizing ETL/ELT pipelines, data warehouses, and enterprise-scale data platforms.

• Knowledge of containerization and orchestration technologies including Docker, Kubernetes, EKS, and Fargate.

• Experience supporting AI/ML workloads, including data pipelines for machine learning, LLM integrations, prompt engineering, vector databases, and RAG architectures.

• Demonstrated ability to lead complex technical initiatives and influence engineering decisions across multiple teams.

• Strong communication and collaboration skills with experience partnering across Engineering, Product, Data Science, and business stakeholders.

#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 offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.:

• Bonus Program

• 401k Retirement

• Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage

• Paid Parental Leave

• Support and Community Involvement

• 14 Paid Company Holidays

• Unlimited Paid Time Off for Exempt Employees

• 96 Hours of Sick Time and 120 Hours of Vacation for Non-Exempt Employees Accrued Each Year

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.

Pay Range

The anticipated compensation for this position is USD $135,910.00/Yr. - USD $223,285.00/Yr. depending on experience and qualifications.

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