Apex Systems
Overview
Data Architect IV
role at
Apex Systems Location: Burbank, CA • Onsite Requirement: Hybrid • 12 Month contract, potential to extend and/or convert Job #: 2084983 What We Do/Project
As part of the Studio Economics transformation, we are establishing a modern, governed, and reusable data foundation to power financial forecasting, title economics, sales planning, and AI-driven insights across the Studios. The Senior Data Architect designs this foundation—ensuring that data models, pipelines, and integration frameworks are scalable, performant, and aligned with enterprise data governance and platform goals. Embedded within the Platform Pod, the Senior Data Architect partners with the Platform Owner, Cloud Architect, data engineering teams, and product-aligned pods to ensure the architecture supports both immediate product needs and long-term platform evolution. This role enables the delivery of reliable, real-time, and reusable data products across multiple Studio Economics workstreams.
Responsibilities / Typical Day In The Role
Design Scalable and Consistent Data Architecture — Define and maintain canonical data models, entity relationships, and semantic layer specifications that ensure consistent use of data across products and domains. Develop and evolve logical and physical data models that support real-time analytics, forecasting, and scenario planning. Collaborate with product-aligned pods to design domain-aligned data products that are modular, governed, and discoverable. Build Reusable, Performant Data Pipelines — Architect data pipelines that support both batch and near real-time processing using AWS-native services (e.g., Glue, Kinesis, Lambda, Step Functions). Guide ingestion, transformation, and enrichment strategies that optimize for resilience, scalability, and lineage traceability. Work with the Cloud Architect to ensure infrastructure and orchestration layers meet pipeline and data SLAs. Embed Governance and Stewardship by Design — Partner with enterprise data governance teams to implement standardized metadata, lineage, and access controls using tools such as Lake Formation, Informatica, or Snowflake. Define data quality rules, validation checkpoints, and anomaly detection processes to support trusted analytics and ML pipelines. Contribute to the enterprise data catalog and enable self-service access through secure, well-documented APIs and schemas. Collaborate Across Platform and Product Pods — Work with Platform Owner to define and deliver shared data services and reusable semantic models that support multi-pod alignment. Support data scientists and analysts by enabling ML/AI-ready data pipelines and structuring data to accelerate model development and deployment. Participate in cross-pod architecture planning to coordinate integration strategies and align on domain boundaries. Must Have Skills / Requirements
Experience in data architecture and engineering, with a focus on cloud-native data platforms and modern analytics workflows. 7+ years of experience designing and delivering data architecture for cloud-based platforms, with strong knowledge of AWS (e.g., Glue, Lambda, Step Functions, Lake Formation) and modern tooling (e.g., Snowflake, Databricks, Informatica). Hands-On Pipeline Design and Orchestration 7+ years of experience designing and optimizing complex data pipelines—ensuring performance, resilience, and real-time capabilities; hands-on experience building batch and streaming pipelines using orchestration frameworks that support real-time and ML/AI-ready processing. Expertise in Canonical Modeling and Semantic Design Proven ability to design scalable, reusable data models and translate them into physical implementations that align with business domains and analytic needs. Functional Knowledge / Skills in the following areas: Think in Domains and Products — Understand business semantics and design models reflecting real-world entities behind Studio workflows. Bridge the Gap Between Models and Platforms — Work across logical design, physical deployment, and infrastructure orchestration in collaboration with Cloud Architects and Engineers. Govern Through Enablement — Embed governance, ensuring compliance, lineage, and quality in design. Build for Reuse and Interoperability — Design assets and APIs for cross-product use and future data science workflows. Promote Transparency and Stewardship — Advocate for shared ownership of data definitions and practices. Cross-Functional Collaboration — Ability to work across engineering, analytics, product, and compliance and communicate decisions clearly. Bias for Structure and Clarity — Resolve semantic conflicts and simplify downstream implementation. Technology Requirements: Deep Data Architecture Experience — Cloud-based platforms with AWS (Glue, Lambda, Step Functions, Lake Formation) and tooling (Snowflake, Databricks, Informatica). Canonical Modeling and Semantic Design Hands-On Pipeline Design and Orchestration Governance and Metadata Awareness Ability to partner with platform and cloud engineering teams to ensure infrastructure supports data reliability, scalability, and SLAs. Data cataloging and self-service APIs experience is a plus.
Interview Process / Next Steps
1st round with HM and lead Data Architect 2nd round with Senior Manager
Apex Benefits Overview
Apex offers a range of benefits including medical, dental, vision, life, disability, ESPP, and a 401(k). We provide an HSA, EAP with counseling, discounts, certification prep, and professional development resources. A Welcome Packet with full benefits details is available from Apex.
EEO Employer
Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, sex, age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, marital status, disability, veteran status, political affiliation, union membership, or any other characteristic protected by law. If you require an accommodation in using our website for a search or application, please contact Employee Services at the email in the job posting.
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Data Architect IV
role at
Apex Systems Location: Burbank, CA • Onsite Requirement: Hybrid • 12 Month contract, potential to extend and/or convert Job #: 2084983 What We Do/Project
As part of the Studio Economics transformation, we are establishing a modern, governed, and reusable data foundation to power financial forecasting, title economics, sales planning, and AI-driven insights across the Studios. The Senior Data Architect designs this foundation—ensuring that data models, pipelines, and integration frameworks are scalable, performant, and aligned with enterprise data governance and platform goals. Embedded within the Platform Pod, the Senior Data Architect partners with the Platform Owner, Cloud Architect, data engineering teams, and product-aligned pods to ensure the architecture supports both immediate product needs and long-term platform evolution. This role enables the delivery of reliable, real-time, and reusable data products across multiple Studio Economics workstreams.
Responsibilities / Typical Day In The Role
Design Scalable and Consistent Data Architecture — Define and maintain canonical data models, entity relationships, and semantic layer specifications that ensure consistent use of data across products and domains. Develop and evolve logical and physical data models that support real-time analytics, forecasting, and scenario planning. Collaborate with product-aligned pods to design domain-aligned data products that are modular, governed, and discoverable. Build Reusable, Performant Data Pipelines — Architect data pipelines that support both batch and near real-time processing using AWS-native services (e.g., Glue, Kinesis, Lambda, Step Functions). Guide ingestion, transformation, and enrichment strategies that optimize for resilience, scalability, and lineage traceability. Work with the Cloud Architect to ensure infrastructure and orchestration layers meet pipeline and data SLAs. Embed Governance and Stewardship by Design — Partner with enterprise data governance teams to implement standardized metadata, lineage, and access controls using tools such as Lake Formation, Informatica, or Snowflake. Define data quality rules, validation checkpoints, and anomaly detection processes to support trusted analytics and ML pipelines. Contribute to the enterprise data catalog and enable self-service access through secure, well-documented APIs and schemas. Collaborate Across Platform and Product Pods — Work with Platform Owner to define and deliver shared data services and reusable semantic models that support multi-pod alignment. Support data scientists and analysts by enabling ML/AI-ready data pipelines and structuring data to accelerate model development and deployment. Participate in cross-pod architecture planning to coordinate integration strategies and align on domain boundaries. Must Have Skills / Requirements
Experience in data architecture and engineering, with a focus on cloud-native data platforms and modern analytics workflows. 7+ years of experience designing and delivering data architecture for cloud-based platforms, with strong knowledge of AWS (e.g., Glue, Lambda, Step Functions, Lake Formation) and modern tooling (e.g., Snowflake, Databricks, Informatica). Hands-On Pipeline Design and Orchestration 7+ years of experience designing and optimizing complex data pipelines—ensuring performance, resilience, and real-time capabilities; hands-on experience building batch and streaming pipelines using orchestration frameworks that support real-time and ML/AI-ready processing. Expertise in Canonical Modeling and Semantic Design Proven ability to design scalable, reusable data models and translate them into physical implementations that align with business domains and analytic needs. Functional Knowledge / Skills in the following areas: Think in Domains and Products — Understand business semantics and design models reflecting real-world entities behind Studio workflows. Bridge the Gap Between Models and Platforms — Work across logical design, physical deployment, and infrastructure orchestration in collaboration with Cloud Architects and Engineers. Govern Through Enablement — Embed governance, ensuring compliance, lineage, and quality in design. Build for Reuse and Interoperability — Design assets and APIs for cross-product use and future data science workflows. Promote Transparency and Stewardship — Advocate for shared ownership of data definitions and practices. Cross-Functional Collaboration — Ability to work across engineering, analytics, product, and compliance and communicate decisions clearly. Bias for Structure and Clarity — Resolve semantic conflicts and simplify downstream implementation. Technology Requirements: Deep Data Architecture Experience — Cloud-based platforms with AWS (Glue, Lambda, Step Functions, Lake Formation) and tooling (Snowflake, Databricks, Informatica). Canonical Modeling and Semantic Design Hands-On Pipeline Design and Orchestration Governance and Metadata Awareness Ability to partner with platform and cloud engineering teams to ensure infrastructure supports data reliability, scalability, and SLAs. Data cataloging and self-service APIs experience is a plus.
Interview Process / Next Steps
1st round with HM and lead Data Architect 2nd round with Senior Manager
Apex Benefits Overview
Apex offers a range of benefits including medical, dental, vision, life, disability, ESPP, and a 401(k). We provide an HSA, EAP with counseling, discounts, certification prep, and professional development resources. A Welcome Packet with full benefits details is available from Apex.
EEO Employer
Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, sex, age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, marital status, disability, veteran status, political affiliation, union membership, or any other characteristic protected by law. If you require an accommodation in using our website for a search or application, please contact Employee Services at the email in the job posting.
#J-18808-Ljbffr