Enterprise Data Architect

at  360insights

ENTERPRISE DATA ARCHITECT

Starting base salary $136,500 – $149,000*

Plus Bonus, Equity & Benefits

• Pay transparency

Our salary ranges are determined by role, level, and location. The range displayed on our job posting reflects the minimum and typical maximum target for new hire salaries for the position, it does not reflect the maximum salary for the role over time. Within the range, individual pay is determined by job-related skills and experience demonstrated during the interview process.

The Enterprise Data Architect works to evolve the experience for our clients and partners through deeper integration across our products and enhanced platform offerings. A key responsibility in ensuring this is possible is enabling our clients and users to access and consume the essential information they need in the manner they need it. To enable this, the Enterprise Data Architect works on developing our data and visualization capabilities which will power the various use cases needed to support our business and clients.

Data architecture, design and modelling:

• Lead the design and implementation of robust and scalable data architectures across enterprise and 360 SaaS platform, with an initial focus on data lakes/warehouses, data pipelines, and master data management, preferably leveraging cloud native stack and features.
• Collaborate with cross-functional teams to understand business requirements and translate them into effective data solutions.
• Create data architecture artifacts and own the architecture governance and practices.
• Promote and articulate the industry design patterns and best practices.
• Contribute to the architecture review of new designs or enhancements.

Data Lake/warehouse and Data Pipeline:

• Oversee the design of the data lake/warehouse infrastructure, ensuring it meets the organization’s scalability, security, and performance requirements.
• Promote and implement best practices for data lake/warehouse governance, metadata management, and data catalogues.
• Design and optimize end-to-end data pipelines for efficient data flow and integration, ensuring data quality and consistency.
• Work closely with data engineers, BI engineers, and reporting analysts to streamline the ETL (Extract, Transform, Load) processes.

Master Data Management:

• Learn the master data domains within the incentive space.
• Define and implement master data management strategies to ensure the accuracy, consistency, and reliability of critical business data.
• Establish and enforce data quality standards, consistency, and processes across the organization.
• Assist with data governance, compliance and privacy initiatives.

Technology Evaluation and Adoption:

• Stay current with emerging technologies and trends in data architecture, recommending and implementing innovations that enhance our data capabilities.
• Evaluate and select appropriate tools and technologies for different components of the data architecture.