Data Architect

Role Purpose

Own the end-to-end data architecture strategy for the organization, leading the design of scalable,

secure, and high-performing data platforms. Act as the technical authority on data modeling,

integration, governance, and infrastructure, while leading a team of data architects/engineers and

guiding cross-functional stakeholders on data-driven initiatives.

Key Responsibilities

Architecture & Strategy

• Define and own the enterprise data architecture strategy, standards, and roadmap, aligned with business objectives.

• Design scalable data models (conceptual, logical, physical) across OLTP, OLAP, and data lake/lakehouse environments.

• Architect data pipelines, ETL/ELT processes, and integration patterns across source systems, data warehouses and downstream applications.

• Evaluate and select appropriate data platforms, tools, and technologies (cloud data warehouses, lakehouses, streaming platforms).

• Define and enforce data governance, data quality, master data management (MDM), and metadata management frameworks.

Technical Leadership

• Lead and mentor a team of data architects, data engineers and/or analysts.

• Review and approve data architecture designs, data models, and technical solutions proposed by the team.

• Set technical direction on data security, privacy, access control, and compliance (e.g. GDPR, data residency requirements).

• Drive adoption of best practices in data modeling, naming conventions, version control, and documentation.

Delivery & Collaboration

• Partner with business stakeholders, product owners, and engineering teams to translate business requirements into data architecture solutions.

• Collaborate with BI/Analytics, Data Science, and application teams to ensure data is structured for reporting, analytics and AI/ML use cases.

• Oversee data migration strategies, including legacy system decommissioning and cloud migration projects.

• Support integration projects, ensuring consistent and reliable data flow across systems (ERP, CRM, third-party applications).

• Participate in architecture review boards and provide technical sign-off on major data initiatives.

Governance & Quality

• Establish data quality standards, monitoring, and remediation processes.

• Define and maintain data catalogs, data lineage, and metadata repositories.

• Ensure architecture decisions support scalability, performance, security, and cost optimization.