Remote/Local Data Architect (15

InnoSoul•Austin, TX

12h•Remote

About The Position

The Data Architect will be responsible for designing and maintaining reporting data models, including fact and dimension structures, semantic layers, and reporting datasets. This role involves defining and documenting data architecture standards, best practices, and governance guidelines, ensuring that data models support business KPIs, operational reporting, dashboards, and advanced analytics. The Data Architect will partner with enterprise architects and data engineering teams to design efficient ETL/ELT pipelines and data integration workflows, translating business requirements into scalable reporting data structures and data flows. Other responsibilities include partnering with cross-functional teams (IT, business, data governance, reporting teams) to align on data strategy and architecture, and providing guidance and mentorship to report developers and analysts on data modeling and best practices. Key duties include leading the design of scalable data solutions, collaborating with reporting teams for consistent definitions and metrics, supporting the creation of reusable data assets for BI tools, working closely with business units and mainframe teams to understand reporting needs, ensuring data accuracy and integrity, establishing and enforcing data governance standards, supporting compliance with security and regulatory requirements, and troubleshooting complex data issues.

Requirements

Strong experience in data modeling (star schema, snowflake schema, semantic modeling).
Hands-on experience with enterprise reporting platforms (e.g., Power BI, Tableau, SSRS).
Ability to translate business requirements into technical data structures.
Skill with Microsoft Office tools, particularly with Word, Excel, Power Point, Visio, and SharePoint
Familiarity with KPI design, business metrics, and analytical methodologies.
Ability to interpret data models, data dictionaries, and technical documentation.
Knowledge of data governance frameworks and metadata management.
Experience in working in fast-paced and ever-changing environments; achieving project's deliverables and deadlines; exercising sound judgment in making critical decisions; analyzing complex information and developing plans to address identified issues.
Skill in interpersonal relationships, including the ability to work with people under pressure, negotiate among multiple parties, resolve conflicts, and establish and maintain effective working relationships with various levels of personnel.

Nice To Haves

Familiarity with mainframe systems (IMS, COBOL files, JCL, batch processes)
Knowledge of local, state, and federal laws and regulations (PII) relevant to data management and data governance
Experience in data focused projects, like moving from Legacy to newer systems.

Responsibilities

Design and maintain reporting data models, including fact and dimension structures, semantic layers, and reporting datasets.
Define and document data architecture standards, best practices, and governance guidelines.
Ensure data models support business KPIs, operational reporting, dashboards, and advanced analytics.
Partner with enterprise architects and data engineering teams to design efficient ETL/ELT pipelines and data integration workflows.
Translate business requirements into scalable reporting data structures and data flows.
Partner with cross-functional teams (IT, business, data governance, reporting teams) to align on data strategy and architecture.
Provide guidance and mentorship to report developers and analysts on data modeling and best practices.
Lead the design of scalable data solutions that support future growth and modernization initiatives.
Collaborate with reporting teams to ensure consistent definitions, calculations, and metrics across the organization.
Support the creation of reusable data assets for BI tools such as Power BI, or similar platforms.
Work closely with business units and mainframe team to understand reporting needs, KPI definitions, and analytical goals.
Ensure data accuracy, consistency, and integrity across reporting environments.
Establish and enforce data governance standards, including naming conventions, metadata, and documentation.
Support compliance with security, privacy, and regulatory requirements.
Troubleshoot complex data issues and provide architectural direction for resolution.