Senior Data Analyst - Disney DTC Sports & ESPN Analytics

Disney Entertainment and ESPN Product & Technology Careers; New York (NY); On-site; USD 125,000 - 167,000; Full time

Job summary

Disney Entertainment & Sports LLC in New York, NY is seeking a Senior Data Analyst to turn data into insights guiding ESPN's direct-to-consumer product strategy. You will own KPI layers, design data models, and build dashboards in Looker to drive business decisions.

You should bring 5+ years in analytics, strong SQL and Python skills, and experience with data warehousing, experimentation, and storytelling for leadership.

Qualifications

• Degree in analytics or equivalent practical experience.
• 5+ years analytics, product analytics or BI.
• Advanced SQL with complex queries.
• Python for data manipulation.
• Experience with data warehousing and dimensional modeling.
• Statistical judgment for baselines and seasonality.
• Experience with experimentation (A/B and multivariate).
• Experience with Looker, Tableau, or similar.
• Strong communication and storytelling.

Responsibilities

• Own and evolve ESPN app KPIs and definitions.
• Design and maintain pre-aggregated metric tables and pipelines.
• Build monitoring to identify real KPI movements.
• QA collaboration with product engineering.
• Create dashboards and self-serve Looker tooling.
• Conduct SQL and Python analyses on multivariate data.
• Partner on experimentation end-to-end.
• Reconcile metrics across teams and align definitions.
• Serve as thought partner for ESPN product teams.
• Communicate results to leadership.

Skills

Advanced SQL

Python

Data Warehousing

Statistical Judgment

Experimentation

Data Visualization

Communication Skills

Product Analytics

Education

Bachelor's in analytics or related field

Tools

Looker

Tableau

Snowflake

Databricks

PySpark

Job description

Job Requirements

SUMMARY

The Disney DTC Sports & ESPN Analytics team is seeking a Senior Data Analyst who will be an exceptional addition to our team. You will be responsible for turning data into information, information into insights, and insights into key business decisions that steer the strategic direction of ESPN's direct-to-consumer product strategy. The right person for this role has exceptional analytical capabilities, thrives in a fast-paced environment, loves problem-solving, is a good communicator, and is passionate about high quality digital product experiences.

RESPONSIBILITIES

• Own and evolve the source-of-truth metric layer for ESPN app performance — headline KPIs (DAU, time spent, watch minutes), their definitions, their dimensional breakouts, and the documented caveats that accompany each
• Design and maintain pre-aggregated metric tables and serving views in Snowflake, and the scheduled pipelines that refresh them, ensuring metrics are correct at every level of aggregation
• Build the monitoring and decomposition logic that identifies when a KPI movement is real and where it is concentrated — baselines, significance thresholds, contribution ranking, and volume-versus-mix splits
• Distinguish genuine behavioral movements from measurement artifacts and instrumentation breakage, and partner with product engineering to close the analytics QA gap on client releases
• Build dashboards and self-serve tooling in Looker that reduce stakeholder reliance on ad-hoc analyst pulls
• Conduct analyses using SQL and Python to access and manipulate multivariate product and behavioral data, and ideate new metrics and analytical approaches for in-app user behavior
• Partner with product and engineering on experimentation end-to-end — translating a product question into a testable hypothesis, selecting primary and guardrail metrics, sizing and powering the test, validating assignment and exposure, analyzing the readout, and diagnosing what happened when a test misbehaves or reads flat
• Reconcile ESPN app metrics across teams and systems, and drive alignment on definitions with Research, Data Product, and data engineering partners
• Serve as a dedicated point of contact and thought partner for ESPN product and product engineering teams, taking projects end-to-end from vague business need to socialized insight
• Communicate results through compelling data storytelling to product leadership and the broader ESPN business

BASIC QUALIFICATIONS

• Degree in an analytical area such as Mathematics, Statistics, Operations Research, Computer Science, Economics, or equivalent practical experience
• 5+ years of relevant work experience in analytics, product analytics, and/or business intelligence
• Advanced SQL — able to read and write complex analytical queries, and to reason about correctness of aggregation logic (for example, why a distinct-count metric cannot be summed across segments)
• Working proficiency in Python for data manipulation, analysis, and pipeline work
• Practical understanding of data warehousing and dimensional modeling — how metric tables are structured, refreshed, and served to downstream consumers
• Applied statistical judgment: constructing baselines, assessing whether a change is meaningful versus noise, and handling seasonality and day-of-week effects
• Hands‑on product experimentation experience — designing and executing A/B and multivariate tests, analyzing results (significance, confidence intervals, minimum detectable effect, guardrail metrics), and diagnosing common failure modes such as sample ratio mismatch, assignment or exposure leakage, interaction effects, and novelty decay
• Experience with data visualization tools (Looker, Tableau, or equivalent) coupled with strong storytelling skills for technical and non‑technical audiences
• Experience taking vague requirements and manipulating them into polished final products
• Strong and effective communication and presentation skills

PREFERRED QUALIFICATIONS

• Hands‑on experience with digital clickstream or behavioral analytics data (Adobe Analytics, Amplitude, or similar), including its identity and measurement limitations
• Experience with Databricks, PySpark, or comparable large‑scale data processing
• Experience establishing metric governance — canonical definitions, reconciliation across teams, and change management on metric logic
• Experience with an experimentation platform (Optimizely, Statsig, Amplitude Experiment, or in‑house) and with scaling experimentation practice across product teams
• Familiarity with identity resolution across web, app, and connected TV, and the practical consequences of cookie‑based measurement
• Prior experience in Sports or Media/Entertainment

Disclaimer

PAY TRANSPARENCY

The hiring range for this position in New York, NY is $124,900 - $167,400 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job‑related knowledge, skills, and experience among other factors. A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

This position is with Disney Entertainment & Sports LLC, which is part of a business we call Disney Entertainment and ESPN Product & Technology.

To learn more about Disney's guidelines on the use of AI for candidates, click here. (https://join.disneycareers.com/global/en/ai-usage)

Disney Entertainment & Sports LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Disney champions a business environment where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a constantly evolving world.

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