Hybrid Data Engineer: Pipelines, ML & Insights

McAfee, Inc.; Frisco (TX); Hybrid; USD 93,000 - 153,000; Full time

Benefits offered by this job

Bonus Program

401k Retirement

Medical, Dental, Vision Coverage

Paid Parental Leave

Unlimited Paid Time Off

Sick Time & Vacation

Job summary

McAfee is seeking a data engineer to transform large-scale data into trusted datasets, insights, and predictive intelligence. The role focuses on building scalable data pipelines and analytic datasets to support analytics, ML, and AI use cases.

This hybrid position is based in Frisco, TX, onsite as needed. The candidate should have 5+ years in Data Engineering, strong Python and SQL, Spark, and cloud data platforms (AWS/Azure/GCP). Relocation assistance is not provided.

Qualifications

• 5+ years hands-on experience in Data Engineering.
• Advanced proficiency in Python and SQL with large-scale data.
• Experience with Apache Spark and ETL/ELT frameworks.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Strong data modeling, data quality, governance fundamentals.
• Interest in moving toward Data Science, ML, and analytics.
• Ability to translate questions into measurable data problems and communicate findings.

Responsibilities

• Design, build, and maintain scalable data pipelines and datasets.
• Ingest and transform telemetry, customer, behavioral, and operational data.
• Ensure data quality, observability, and governance.
• Use Python, SQL, Spark and cloud data tech to derive insights.
• Develop features, metrics, cohorts, and segments.
• Progressively develop statistical and ML models.
• Apply NLP, embeddings, and Generative AI where relevant.
• Collaborate with Engineering and Product to translate questions into data problems.

Skills

Data Engineering

Python

SQL

Analytics mindset

Communication

Problem solving

Education

Degree in Data Science / ML / Statistics / Applied Math / CS

Tools

Apache Spark

ETL/ELT frameworks

Pandas

NumPy

scikit-learn

Job description

McAfee is seeking a data engineer to transform large-scale data into trusted datasets, insights, and predictive intelligence. The role focuses on building scalable data pipelines and analytic datasets to support analytics, ML, and AI use cases.

This hybrid position is based in Frisco, TX, onsite as needed. The candidate should have 5+ years in Data Engineering, strong Python and SQL, Spark, and cloud data platforms (AWS/Azure/GCP). Relocation assistance is not provided.