Data Architect

Stord’s mission is to make supply chains a competitive advantage with best-in-class port-to-porch logistics combined with the integrated technology that brands need to connect, orchestrate, and optimize their supply chains. We’ve pioneered Cloud Supply Chain, which combines all of the digital and physical elements of logistics that leading businesses need in a unified offering.

With Cloud Supply Chain, Stord is enabling companies to compete and grow with world-class logistics – including warehousing, freight and fulfillment – in a single, integrated platform that’s available exactly when and where they need it. Hundreds of B2B and B2C companies like Body Armor, Advanced AutoParts and Dollar General use Stord to make their supply chains perform with the speed, flexibility and ease of the cloud.

Our rapidly growing team is headquartered in the heart of Atlanta’s vibrant tech community and is led by former operators from Amazon, XPO, Ryder, Coyote, Convoy, and Manhattan Associates. Stord is backed by over $325M in funding from Kleiner Perkins, BOND, Founders Fund, D1 Capital, Salesforce Ventures, Susa Ventures, Lux Capital, Lineage Logistics, and Franklin Templeton Investments at a unicorn valuation of over $1.3 billion.

Come help us help businesses out-deliver their competition with Cloud Supply Chain.

About the Data Architect Position: 

STORD is looking for a Data Architect to join the Site Reliability Engineering team. This role will focus on standardizing and implementing best practices across our software teams and databases. This person will build and own data pipelines, identify and implement database best practices, and work closely with our data and engineering teams to optimize and scale our data.  

What You'll Do:

Data Strategy and Planning

• Standardize software development database architecture across multiple enterprise systems by setting and maintaining a standard
• Drive and own schema design, code review, SQL query tuning
• Develop and implement a data strategy aligned with business objectives.
• Collaborate with stakeholders to understand business requirements and define data architecture principles and standards.
• Create a roadmap for the evolution of the data architecture over time.

Data Warehousing and Business Intelligence

• Design and oversee the implementation of data warehouses.
• Work with business intelligence teams to ensure data availability for reporting and analytics.
• Optimize data structures to support efficient querying and reporting.
• Ability to identify risks and dependencies to database decisions and how it empowers data and analytics

Data Modeling

• Design and develop conceptual, logical, and physical data models.
• Define data entities, relationships, and attributes to represent business concepts accurately.
• Ensure data models adhere to industry best practices and standards.

Database Management

• Influence the selection of appropriate database technologies based on project requirements and ensure high availability.
• Define database structures, tables, and indexes to optimize data storage and retrieval.
• Oversee database performance tuning and optimization.
• Identify areas of improvement, and implement optimization of databases to ensure optimal performance and cost efficiency
• Recommend and coordinate upgrades for existing database systems and ensure disaster recovery

Data Integration

• Design and implement data integration solutions to facilitate the flow of data across systems.
• Define data mapping, transformation, and cleansing processes.
• Ensure data consistency and integrity during integration.
• Build and own data pipelines of enterprise software 

Data Security and Privacy

• Establish and enforce data security policies and access controls.
• Implement encryption, authentication, and authorization mechanisms to safeguard sensitive data.
• Ensure compliance with security policies, own obfuscation protocols and protect database infrastructure and assets 

Data Governance

• Define and implement data governance policies, procedures, and standards.
• Establish data quality frameworks and monitoring processes.
• Facilitate data stewardship and ownership initiatives.

Technology Evaluation and Adoption

• Improve data architecture by tracking emerging technologies and evaluating their applicability to business goals and operational requirements
• Evaluate and recommend new tools and technologies that align with organizatio