Senior Data Engineer - Consumer Subscriptions

xAI•Palo Alto, CA

1d•$180,000 - $440,000

About The Position

We’re seeking a Senior Data Engineer to join the Consumer Subscriptions team. You will own the analytics foundation for X Premium and SuperGrok — one of X’s fastest-growing revenue organizations. You will dive deep into the entire consumer subscription ecosystem, turning massive-scale data into clear, actionable insights that drive strategic decisions, optimize revenue, and shape product direction. This high-impact role combines rigorous statistical analysis, compelling visualization, and hands-on data engineering to monitor performance, measure impact, surface opportunities, and ensure every initiative moves the needle.

Requirements

5+ years of experience as a data analyst (or equivalent) with a proven track record in revenue, subscription, or growth analytics.
Strong SQL and Python proficiency (pandas, numpy, etc.) for data extraction, cleaning, and analysis.
Deep experience with statistical methods, A/B testing, cohort analysis, and causal inference.
Strong familiarity with subscription metrics and modeling (LTV, churn, retention, conversion, revenue attribution, etc.).
Skilled at building intuitive dashboards and visualizations (Looker, Tableau, Metabase, or Python-based tools).
Ability to handle large-scale data with a strong emphasis on accuracy, rigor, and storytelling.

Nice To Haves

Prior work in consumer subscriptions, billing, payments, or monetization analytics at scale.
Experience with BigQuery and real-time analytics pipelines.
Strong product intuition and the ability to connect data insights directly to business outcomes.

Responsibilities

Own end-to-end analysis of the consumer subscriptions ecosystem — including acquisition, conversion, retention, churn, revenue, pricing, promotions, bundles, and global performance.
Build and maintain high-impact dashboards and visualizations that give the team real-time visibility into key metrics and trends.
Perform deep statistical analysis and experimentation to quantify the impact of new features, offers, communications, and market expansions.
Identify where the team should focus next by uncovering growth opportunities, user behavior patterns, and optimization levers.
Design and run ongoing monitoring systems and automated audits to ensure data accuracy, integrity, and compliance at scale.
Write efficient code (SQL, Python, etc.) to extract, transform, and analyze complex datasets from multiple sources.
Translate complex findings into clear, compelling narratives and recommendations that influence engineering, product, and business strategy.