Tential Solutions
As part of the 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 enterprise. The
Senior Data Analyst
plays a pivotal role in shaping that foundationtranslating 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 strategyensuring reusability, governance compliance, and analytical readiness. Responsibilities 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. 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. 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. 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.
Qualifications
Proven expertise in data modeling techniques (relational, dimensional, wide-table for ML, data vault) and mapping business processes to data structures. 7-10+ years of experience in data modeling and related data roles. Strong proficiency in SQL, data profiling, and transformation tools (dbt, Informatica, AWS Glue). Familiarity with distributed data processing and analytics platforms (Snowflake, Databricks, AWS-native analytics stack). Experience translating product features and user stories into well-defined data model requirements.
Technology Requirements
Proven expertise in data modeling techniques (relational, dimensional, wide-table for ML, data vault) and mapping business processes to data structures. Strong proficiency in SQL, data profiling, and transformation tools (dbt, Informatica, AWS Glue). Experience in data quality frameworks, validation automation, and reconciliation methods. Familiarity with distributed data processing and analytics platforms (Snowflake, Databricks, AWS-native analytics stack). Demonstrated ability to align cross-team requirements into unified, reusable, and governed data solutions. Experience translating product features and user stories into well-defined data model requirements.
Location and Schedule
Hybrid schedule 3 days on-site (Burbank, CA)
Job Details
Seniority level: Mid-Senior level Employment type: Contract Job function: Information Technology
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Senior Data Analyst
plays a pivotal role in shaping that foundationtranslating 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 strategyensuring reusability, governance compliance, and analytical readiness. Responsibilities 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. 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. 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. 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.
Qualifications
Proven expertise in data modeling techniques (relational, dimensional, wide-table for ML, data vault) and mapping business processes to data structures. 7-10+ years of experience in data modeling and related data roles. Strong proficiency in SQL, data profiling, and transformation tools (dbt, Informatica, AWS Glue). Familiarity with distributed data processing and analytics platforms (Snowflake, Databricks, AWS-native analytics stack). Experience translating product features and user stories into well-defined data model requirements.
Technology Requirements
Proven expertise in data modeling techniques (relational, dimensional, wide-table for ML, data vault) and mapping business processes to data structures. Strong proficiency in SQL, data profiling, and transformation tools (dbt, Informatica, AWS Glue). Experience in data quality frameworks, validation automation, and reconciliation methods. Familiarity with distributed data processing and analytics platforms (Snowflake, Databricks, AWS-native analytics stack). Demonstrated ability to align cross-team requirements into unified, reusable, and governed data solutions. Experience translating product features and user stories into well-defined data model requirements.
Location and Schedule
Hybrid schedule 3 days on-site (Burbank, CA)
Job Details
Seniority level: Mid-Senior level Employment type: Contract Job function: Information Technology
#J-18808-Ljbffr