Data Architect

Job Description

Insight Global is seeking a Data Architect to own the design and development of our enterprise data platform. This role will partner closely with Finance, Label Services, Marketing, Operations, and Executive Leadership to define data standards, establish source-of-truth governance, and drive key architectural decisions.

You will design the data warehouse architecture, lead the integration and reconciliation of data across multiple systems, and establish scalable frameworks for entity resolution, reporting, and analytics. Additionally, you will manage a small team of data engineers and contractors responsible for building and maintaining the data platform and transformation pipelines.

This role requires a strategic leader who can navigate complex data ecosystems, align technical solutions with business needs, and evaluate and implement the right tools and technologies to support long-term growth.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

3–8+ years of experience in Data Engineering, Analytics Engineering, Data Architecture, or a related field. We value demonstrated ownership and impact in production environments over years of tenure. Candidates should be able to showcase hands-on experience designing data models, integrating complex systems, and making architectural decisions in real-world settings.

Strong engineering fundamentals with the ability to independently design systems, write and troubleshoot code, build integrations, and reason through complex data architecture challenges. Experience using AI-assisted development tools is a plus but should complement—not replace—core technical expertise.

Deep expertise in complex data integration across diverse and heterogeneous data sources, including aggregation, entity resolution, and data reconciliation. Proven ability to navigate and articulate trade-offs between approaches such as deterministic versus probabilistic matching, human-in-the-loop review processes, source-system keying strategies, and conflicting sources of truth.

Leadership experience managing and mentoring technical teams, particularly in ambiguous data integration and transformation initiatives where requirements, business rules, and source data may be incomplete or poorly documented.

Proven track record integrating with multiple external SaaS platforms through APIs, flat-file exports, or third-party connectors. Comfortable working with inconsistent, undocumented, and vendor-specific data structures.

Exceptional communication and stakeholder management skills, with the ability to effectively collaborate across technical and non-technical audiences, including engineering, analytics, finance, and executive leadership teams.

Experience owning and documenting architectural decisions, creating clear, scalable documentation that supports long-term maintainability and knowledge sharing across teams.

Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related discipline preferred. Equivalent practical experience will also be considered. Experience working with music industry data platforms and datasets such as FUGA, Luminate, Chartmetric, Mediabase, RightsHub, royalty systems, and DSP reporting is highly preferred but not required.

Ability to quickly learn complex business domains and translate business processes into scalable data models and analytics solutions.

Experience designing AI-enabled analytics products, including natural language querying, semantic search, AI-generated reporting, and workflow automation.

Background in financial data attribution, including cost allocation, revenue attribution, royalty calculations, and financial reconciliation across multiple data sources.

Experience supporting data-driven decision-making in media, entertainment, music, or rights-management environments.