Data Architect

Core Responsibilities

Architecture Strategy & Planning

• Establish and guide long-term data design principles, including standards, ownership structures, and governance approaches.
• Review the current ecosystem of applications, databases, and integrations to uncover inefficiencies and recommend improvements.
• Convert business needs into a structured roadmap supporting analytics, intelligent automation, and enterprise reporting.
• Produce and maintain artifacts such as data models, architecture diagrams, and design documentation.

Data Design & Integration

• Build and manage scalable data structures supporting operational and analytical use cases.
• Oversee development of data movement processes, integrations, and pipelines across hybrid environments.
• Apply contemporary design patterns (e.g., layered data refinement approaches, columnar storage formats, and distributed architectures).
• Evaluate third-party solutions to ensure alignment with internal standards.

Data Governance & Integrity

• Define and promote best practices related to data oversight, including lineage tracking, metadata, and master data strategies.
• Implement controls to monitor and improve accuracy, consistency, and reliability of information assets.
• Ensure alignment with applicable data protection and confidentiality requirements.
• Work alongside security and risk functions to maintain compliant and auditable data processes.

Collaboration & Leadership

• Engage with senior stakeholders and business units to identify opportunities for leveraging data.
• Simplify and communicate technical concepts for non-technical audiences.
• Provide mentorship and direction to technical team members.
• Stay informed on evolving tools, trends, and methodologies within the data space.

Qualifications

• Degree in a technology-related discipline or equivalent experience.
• Several years of experience in data-focused roles such as architecture or engineering, preferably within a structured, service-oriented organization.
• Strong background in data modeling, storage solutions, and large-scale data processing.
• Experience working with cloud-based data ecosystems and modern analytics platforms.
• Familiarity with current data design approaches, including distributed storage formats and layered data processing techniques.
• Understanding of governance concepts such as data quality management, lineage, and centralized data definitions.
• Strong problem-solving ability and attention to detail.
• Proven ability to work across both technical and business teams and influence decision-making.
• Experience handling sensitive or regulated data environments.
• Exposure to enterprise business systems (financial, CRM, HR, or document management platforms) is a plus.