Data Architect

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Data Architect

Salary: $135,000-$180,000

Overview

As a Data Architect, you will play a critical role in defining and executing the organization's data architecture strategy. You will ensure data platforms, systems, and frameworks are designed for scalability, performance, security, and business value. This role serves as the primary authority on data architecture, data modeling, warehousing, governance, and analytics, helping drive modernization initiatives and enabling data-driven decision-making across the enterprise.

This position combines strategic leadership with deep technical expertise, ensuring technology investments align with organizational goals and deliver measurable business outcomes.

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Responsibilities

• Define and maintain the enterprise data architecture strategy, ensuring alignment between business objectives and technical data solutions.
• Serve as the principal architect for enterprise data platforms, with a strong focus on cloud-based data services, ETL/ELT processes, and distributed data architectures.
• Partner closely with engineering, product, and business teams to design scalable data warehouses, data lakes, and high-performance database systems.
• Establish standards for data modeling, metadata management, master data management, and data exchange to ensure consistency across platforms.
• Lead data modernization initiatives, including migration from legacy systems to modern cloud-native data architectures.
• Collaborate with DevOps and platform teams to improve data pipeline automation, monitoring, observability, and deployment processes.
• Provide architectural leadership for high-volume transactional and analytical data systems.
• Partner with security and compliance teams to ensure data privacy, governance, encryption, resiliency, and regulatory adherence across the technology landscape.
• Lead architecture and design reviews, mentor data engineers and architects, and promote best practices in modern data engineering.
• Support technology and business leadership in defining data roadmaps, evaluating emerging technologies, and evolving data capabilities to meet changing business needs.
• Drive enterprise-wide data governance initiatives and establish standards for data quality, consistency, and lifecycle management.

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Required Skills and Experience

• Proven experience designing, implementing, and maintaining large-scale cloud-based data architectures.
• Deep expertise in modern cloud data platforms and services, including data warehouses, data lakes, distributed storage, and analytics platforms.
• Strong experience with data modeling methodologies, including entity relationship modeling and dimensional modeling.
• Extensive knowledge of ETL/ELT design, data integration, transformation frameworks, and pipeline orchestration.
• Hands-on experience with programming and scripting languages commonly used for data processing, such as Python, SQL, Java, or similar technologies.
• Strong understanding of both relational and NoSQL database platforms.
• Experience optimizing database performance, scalability, reliability, and data quality processes.
• Excellent analytical, problem-solving, and communication skills, with the ability to bridge technical and business priorities.
• Ability to think strategically while remaining hands-on in architecture and implementation activities.
• Experience designing and managing enterprise data warehouses, data lakes, and analytics environments.
• Familiarity with data integration standards and electronic data exchange processes.
• Experience with business intelligence, reporting, and data visualization platforms.

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Technology Environment

Experience with technologies similar to the following is preferred:

Cloud & Infrastructure

• Cloud platforms (AWS, Azure, Google Cloud Platform, or equivalent)
• Containerized and serverless architectures
• Infrastructure-as-Code tools

Data & Analytics

• Relational databases
• NoSQL databases
• Data warehouses and data lakes
• Data visualization and business intelligence tools

Development

• Java, Python, TypeScript, or similar programming languages
• Modern application frameworks and services

Integration

• REST APIs
• JSON and other data interchange formats
• Authentication and identity management solutions

DevOps & Automation

• Source control platforms
• CI/CD pipelines
• Infrastructure automation and monitoring tools

Project Delivery

• Agile delivery methodologies
• Collaboration and project management platforms

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Preferred Qualifications

• Experience establishing enterprise data governance frameworks and standards across multiple business functions.
• Exposure to big data platforms, streaming architectures, event-driven systems, and messaging technologies.
• Familiarity with data security, privacy, and regulatory compliance requirements.
• Knowledge of real-time analytics and large-scale data processing environments.
• Experience mentoring technical teams and influencing architectural decisions across organizations.
• Industry experience in financial services, payments, healthcare, retail, loyalty, customer engagement, or other data-intensive sectors is a plus.

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Key Competencies

• Ability to design and implement scalable, secure, and resilient enterprise data architectures.
• Deep understanding of modern data engineering, database technologies, analytics platforms, and cloud ecosystems.
• Strong leadership capabilities with experience guiding architecture initiatives and establishing best practices.
• Excellent stakeholder management and communication skills across technical and non-technical audiences.
• Strategic mindset with the ability to balance long-term architecture goals and near-term business needs.
• Proven ability to solve complex data challenges and drive modernization and transformation initiatives.
• Commitment to data quality, governance, security, and operational excellence.