Enterprise Data Architect Consultant

CG Infinity•Sugar Land, TX

About The Position

CG Infinity is seeking a strategic and hands-on Enterprise Data Architect to design, build, and lead the implementation of a scalable, enterprise-wide data warehouse. This role will be responsible for developing a modern data architecture from the ground up, integrating multiple systems and business units into a unified data ecosystem that drives analytics, reporting, and business decision-making. The ideal candidate combines deep technical expertise with strong business acumen, capable of leading discovery efforts, defining priorities, and ensuring data solutions are aligned with organizational goals. This individual will also play a key leadership role in establishing data governance, master data management (MDM), and enterprise data standards.

Requirements

8+ years of experience in data architecture, data engineering, or enterprise data management roles.
Proven experience building an enterprise data warehouse from scratch spanning multiple systems and business units.
Strong experience with data modeling, ETL/ELT design, and data integration frameworks.
Hands-on experience with cloud data platforms (e.g., Azure, AWS, or GCP).
Demonstrated expertise in: Data Governance frameworks, Master Data Management (MDM), Data quality and metadata management
Experience leading discovery sessions and requirements gathering workshops with senior stakeholders.
Strong understanding of enterprise systems (ERP, CRM, operational apps) and integration patterns.
Excellent communication, facilitation, and leadership skills.

Nice To Haves

Experience in consulting environments or multi-client, multi-business unit organizations.
Industry experience in oil & gas or chemical sectors, with an understanding of upstream, midstream, downstream, or refining operations.
Familiarity with modern data tools (e.g., Snowflake, Databricks, Azure Synapse, Power BI, Tableau).
Experience implementing data lakes, lakehouse architectures, or hybrid data ecosystems.
Knowledge of Agile and iterative delivery methodologies.
Relevant certifications (e.g., Azure Data Architect, AWS Data Analytics, DAMA CDMP).

Responsibilities

Design and implement a scalable, secure, and high-performance enterprise data warehouse from inception.
Define the end-to-end data architecture, including data ingestion, transformation, storage, integration, and consumption layers.
Establish architectural standards, frameworks, and best practices aligned with business and technology strategies.
Evaluate and recommend technologies (cloud platforms, ETL/ELT tools, data lakes, warehouses) to support long-term scalability.
Lead discovery sessions with business and technical stakeholders to identify high-value use cases, priorities, and dependencies.
Translate business requirements into technical data models, data flows, and architecture designs.
Ensure alignment between data solutions and business objectives, including KPIs, reporting, and analytics needs.
Develop and maintain a data roadmap with clearly defined phases, milestones, and deliverables.
Oversee development of integrated data pipelines that connect disparate systems (ERP, CRM, operational systems, third-party platforms).
Define and implement data models (conceptual, logical, physical) to support analytics and reporting.
Establish data quality frameworks and ensure reliability, consistency, and integrity of enterprise data.
Ensure performance optimization and scalability of the data environment.
Develop and implement enterprise data governance policies, standards, and controls.
Lead Master Data Management (MDM) initiatives to standardize key business entities across systems.
Define data ownership, stewardship, and accountability models across business units.
Ensure compliance with regulatory, security, and data privacy requirements.
Act as a trusted advisor to executive leadership, including the CTO and business leaders.
Communicate complex technical concepts clearly to non-technical stakeholders.
Lead cross-functional teams, including data engineers, analysts, and business users.
Drive adoption of data solutions across the organization through change management and stakeholder alignment.