Qualifications
Responsibilities
Benefits
About the Role
Build andvalidatethe data logic behind core business KPIs translating business definitions into certified analytical models across multiple dimensions.
Perform end-to-end data reconciliation validatinganalytical datasets against finance and operational source-of-truth systems, investigating discrepancies, and ensuring accuracy of reported metrics.
Conduct customer lifecycle analysis defining and measuring customer populations, segmenting behavior across acquisition, engagement, and renewal stages, andidentifyingdrivers of key business outcomes.
Build waterfall and funnel analyses decomposing aggregate metric movements into contributing factors, quantifying the impact of each, and presenting findings to leadership in a clear and actionable format.
Build andmaintaindata models and transformation logic working in Databricks to create, migrate, and backfill analytical tables,validatedata transformations, and ensure consistency between raw and curated data layers.
Produce andmaintainautomated dashboards and reports building executive-facing visualizations that track business performance across multiple data sources with automated refresh pipelines.
Conduct root cause analysis on metric anomalies investigating unexpected movements in KPIs, tracing issues through multiple data layers, and producing actionable findings for business stakeholders.
Deliver ad-hoc analysis for senior leadership responding to executive requests with data-driven insights on topics such as customer sizing, audience segmentation, and business performance deep dives.
Document data lineage and business logic mapping how metrics flow from source systems through transformation layers to final reporting, ensuring traceability and auditability of all certified KPIs.
Collaborate cross-functionally with Data Engineering, Finance, and Data Stewards to certify data logic before it enters production reporting, and flag data quality issues proactively.
About You
You have 5+ years of experience in data analytics, business intelligence, or a related quantitative field.
You have deepexpertisein subscription or SaaS business metrics including retention rate, churn, auto-renewal, trial conversion, LTV, and bookings ideally in a consumer technology or eCommerce context.
Data and coding fluency you are a self-starter comfortable using SQL, Python, and generative AI tools to access data and deliver analysis independently.
You have hands-on experience with Databricks (SQL,Python,PySpark, Delta Lake) and can write, review, and troubleshoot complex analytical queries and data pipelines.
You have experience with BI and reporting platforms particularly Power BI.
You have experience with data validation and reconciliation comparing data across source systems,identifyingdiscrepancies, and documenting business rules that govern metric calculations.
You are comfortable performing root cause analysis diagnosing why a metric moved, tracing issues through multiple data layers, and presenting findings clearly to both technical and non-technical stakeholders.
You can translate ambiguous business questions into structured analytical approaches scoping the data needed, defining assumptions, and delivering concise answers under time pressure.
You have experience working in agile environments managing your own backlog across 2-week sprints, balancing recurring reporting with project work, and communicating progress and blockers proactively.
#LI-Hybrid
The starting pay range for this position is $122,010.00-$165,070.00. McAfee takes into consideration an individual’s skillset, experience and location in making final salary determinations. For further details, please discuss with the Talent Acquisition Partner.About McAfee
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