Data Analyst

McAfee•Frisco, TX

9d•Hybrid

About The Position

Role Overview: The McAfee Analytics Platform & Enablement team is expanding its capabilities to strengthen data-driven decision-making across a global direct-to-consumer business serving over 400 million customers. We are looking for a Data Analyst who will play a key role in building scalable data solutions and uncovering actionable insights that drive marketing performance and business growth. We're seeking someone curious about data, passionate about building analytical solutions, and eager to become a trusted data expert who empowers others through insight and clarity. This is a Hybrid Position located in Frisco, TX. We are only considering candidates within a commutable distance to the Frisco office. You will be required to be onsite on an as-needed basis; when not working onsite, you will work from your home office. About the Role: In this role, you will leverage your analytical, technical, and problem-solving skills to: Discover, transform, and analyze large datasets to extract meaningful insights. Build and maintain data tools, dashboards, and reports that enable marketers, product managers, analysts, and leaders to monitor key metrics and identify opportunities. Collaborate with cross-functional teams to design and optimize data structures that support reporting and analytics needs. Serve as a subject matter expert on data definitions, architecture, and best practices within the organization. About you: Minimum of 3 years of progressively responsible experience in data analysis, data engineering, or analytics-driven solution development.

Requirements

Minimum of 3 years of progressively responsible experience in data analysis, data engineering, or analytics-driven solution development.
Demonstrated proficiency in SQL and Python (3+ years), with extensive experience performing data exploration, transformation, and analysis across large-scale relational and analytical datasets.
Proven experience designing, developing, and maintaining end-to-end data pipelines (ETL/ELT), including the automation of data workflows, data ingestion processes, and data quality controls.
Strong understanding of data architecture principles, including logical and physical data modeling, data structure design, and data integration best practices.
Demonstrated ability to ensure data integrity and consistency across multiple data sources, and to translate business requirements into scalable, reliable, and well-structured data solutions.
Hands-on experience working with Databricks, cloud platforms (Azure or AWS), and distributed computing technologies such as PySpark or Spark SQL.
Solid background in statistical analysis and experimentation, including hypothesis testing methodologies (Frequentist, Bayesian, or multivariate A/B testing).
Familiarity with data governance practices, metadata management, and documentation standards to support transparency, consistency, and operational excellence.
Exceptional written and verbal communication skills, including the ability to convey complex technical concepts to diverse technical and non-technical audiences.

Responsibilities

Discover, transform, and analyze large datasets to extract meaningful insights.
Build and maintain data tools, dashboards, and reports that enable marketers, product managers, analysts, and leaders to monitor key metrics and identify opportunities.
Collaborate with cross-functional teams to design and optimize data structures that support reporting and analytics needs.
Serve as a subject matter expert on data definitions, architecture, and best practices within the organization.