Enterprise Data Architect Consultant

Key Responsibilities

• Design and implement a scalable, secure, and high-performance enterprise data Lakehouse from inception.
• Define the end-to-end data architecture, including data ingestion, transformation, storage, integration, and consumption layers.
• Evaluate and recommend technologies (cloud platforms, ETL/ELT tools, data lakes, Lakehouses) 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.

Required Qualifications

• 8+ years of experience in data architecture, data engineering, or enterprise data management roles.
• Proven experience building an enterprise data Lakehouse 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.

Preferred Qualifications

• 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).