Enterprise Data Architect

This position is based in the Charlotte, NC area with a hybrid work schedule of three days per week in office (Tues, Wed, Thurs). Candidates must be located in the Charlotte area or willing to relocate to be considered for this position.

At LendingTree, we believe that data is at the core of everything we do. We are a forward-thinking, innovative organization that leverages data to deliver insights and make informed decisions. We are looking for an experienced Enterprise Data Architect to join our team and help us build and scale our data infrastructure to support the growing needs of the business. 

Job Summary: 

As Enterprise Data Architect, you will be an individual contributor who will help shape the overall data strategy and architecture, designing scalable, high-performance data systems that align with business objectives. You will play a crucial role in ensuring that our data architecture supports both operational, analytical & integration needs, fosters innovation, and adheres to best practices and compliance standards. The successful candidate will work closely with staff data leads, developers, analytics teams, and business stakeholders to ensure the data platform supports our needs effectively and efficiently.  

Key Responsibilities: 

• Snowflake Platform: 
  • Stay informed about the Snowflake product roadmap and bring innovative ideas back to tech leads. 
  • Monitor and report on Snowflake credit usage, highlighting anomalies and working with teams to optimize compute cost. 
  • Help us maintain a robust security and privacy posture, particularly concerning roles and PII data, including automatic detection and masking policies for sensitive data. 
  • Facilitate the optimal deployment of Snowflake by working with data engineering teams to collaboratively set standards. 
  • Liaise between Developer teams and Operations as needed. 
  • Enhance business support by simplifying the onboarding process and providing ongoing training opportunities in Snowflake. 

• Data Integration  
  • Help design efficient data pipelines that ensure data is moved from raw formats to structured formats ready for consumption by analytics, reporting, integration and ML models. 
  • Ensure data integration processes can handle real-time, batch, and event-driven data streams. 
  • Optimize pipelines for scalability, performance, and reliability, ensuring they can handle the volume, velocity, and variety of data required by the organization. 
  • Work with DataOps teams to automate and monitor the data pipelines to ensure minimal downtime and fast recovery. 

• Data Modeling & Data Platform Optimization 
  • Collaborate with data engineering teams and domain SMEs to design and implement unified data models that optimize storage and query performance across systems 
  • Optimize data architecture and pipelines for performance as data volumes and usage grow. 
  • Monitor and identify bottlenecks in data infrastructure, implementing strategies such as indexing, partitioning, and other performance-enhancing techniques to ensure fast data retrieval. 
  • Scale data systems and infrastructure to handle increasing workloads in terms of both volume and complexity. 
  • Track and report on credit usage, address anomalies, and collaborate with teams to optimize compute and spend across data technologies. 
  • Proactively identify and resolve performance bottlenecks, ensuring the scalability of data systems to support growing data volumes. 

Qualifications: 

• Bachelor’s or master’s degree in computer science, Information Systems, or related field. 

• 10+ years of data engineering experience, with at least 8 years of data architecture experience designing, building, and maintaining large-scale data infrastructure. 

• Expertise with Snowflake or similar cloud-based data war