Senior Data Analyst

  • Burbank, CA
  • Posted 1 day ago | Updated 1 day ago

Overview

Hybrid
$70 - $80
Contract - W2
Contract - 10 Month(s)

Skills

Advanced Analytics
Data Analyst
data modeling
relational
dimensional
wide-table
ML
data vault
SQL
data profiling
transformation
Informatica
AWS Glue
data processing
analytics
Snowflake
Databricks
AWS-native
product
user stories
requirements
Machine Learning (ML)
Use Cases
Snow Flake Schema
Meta-data Management
Forecasting
Data Validation

Job Details

One of the largest media and entertainment corporations in the world is looking to hire a Senior Data Analyst in Burbank, CA, for a 10-month contract on W2.

  • Hybrid schedule 3 days on-site.
  • Possibility For Extension / Conversion? Yes

As part of the Studio Economics transformation, we are building a modern, governed, and reusable data foundation to power financial forecasting, title economics, content sales planning, and AI-driven insights across the Studios.

The Senior Data Analyst plays a pivotal role in shaping that foundation translating product requirements into robust, scalable data models that serve both immediate application needs and long-term analytical and AI objectives.

Embedded within the Platform Pod, this role works closely with Application Designers, Platform Engineers, the Senior Data Architect, and product-aligned pods to ensure application-specific data models integrate seamlessly with the enterprise data platform. They act as the primary bridge between feature-level requirements and platform-level data strategy ensuring reusability, governance compliance, and analytical readiness.

Job Responsibilities / Typical Day in the Role

Lead Data Analysis for Application & Platform Alignment

  • Translate product features and user stories into well-defined data model requirements that support application workflows and downstream analytics.
  • Partner with Application Designers and Engineers to profile, assess, and validate source data, ensuring it meets both functional and non-functional requirements.
  • Collaborate with the Senior Data Architect to align application data models with canonical and semantic models across domains.

Ensure Long-Term Analytical & AI Enablement

  • Design data structures and pipelines that serve both operational application needs and future analytical/AI use cases.
  • Anticipate and define data capture, transformation, and enrichment requirements to support predictive modeling, forecasting, and advanced analytics.
  • Recommend optimizations that improve data quality, timeliness, and completeness for decision-making.

Governance, Quality, and Documentation

  • Partner with enterprise data governance teams to apply metadata, lineage, and access control standards.
  • Define and execute data validation, profiling, and reconciliation processes to ensure trusted results.
  • Maintain documentation of data definitions, mapping specifications, and lineage diagrams for both applications and analytical datasets.

Cross-Pod Collaboration and Mentorship

  • Lead cross-pod workshops to resolve semantic conflicts, promote reusable data assets, and ensure consistent application of standards.
  • Mentor junior analysts and support teams in data discovery, mapping, and quality assessment best practices.
  • Represent the Platform Pod s data perspective in architecture boards, product councils, and design reviews.

Years of experience:

  • 7+ years of experience as a Data Analyst, Data Modeler, or similar role in enterprise-scale, cloud-based environments.

Must Have Skills / Requirements

7-10+ years of experience:

  1. Proven expertise in data modeling techniques (relational, dimensional, wide-table for ML, data vault) and mapping business processes to data structures.
  2. Strong proficiency in SQL, data profiling, and transformation tools (e.g., dbt, Informatica, AWS Glue).
  3. Familiarity with distributed data processing and analytics platforms (e.g., Snowflake, Databricks, AWS-native analytics stack).
  4. Experience Translating product features and user stories into well-defined data model requirements.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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