• Design and implement scalable data ingestion and transformation pipelines using Databricks and cloud platforms • Lead architecture decisions for modern data platforms, including Medallion Architecture and Lakehouse patterns • Build and maintain ETL/ELT pipelines using Python and SQL, following engineering best practices • Lead and mentor engineering teams, coordinating deliveries and driving technical standards • Establish and evolve CI/CD pipelines and Infrastructure as Code (IaC) practices for data platforms • Partner with clients and stakeholders to translate business requirements into scalable data solutions • Champion data governance, quality, and security using tools such as Unity Catalog • Contribute to platform modernization initiatives, including Data Warehouse to Lakehouse migrations • Apply Agile methodologies to plan, iterate, and deliver data engineering projects effectively

• Build and grow customer-facing data products • Build AI-powered and agentic analytics tools • Build the backend services, APIs, and query layer that power these products • Partner with product and design to translate customer and business needs into reliable, performant, data-intensive features

• Designs and develops moderately complex queries, objects, ETL packages, reporting structures, and other objects necessary to support detailed analysis and self-service reporting needs. • Collaborates with analytics and business teams to create and improve data models that feed BI tools, increasing data accessibility, and fostering data-driven decision making across the organization. • Takes ownership of the health, reliability, and security of the data platform by designing and implementing processes and solutions that proactively monitor data delivery across the full pipeline — ensuring data is accurate, complete, consistent, and timely from source ingestion through gold layer curation. • Investigates, diagnoses, and resolves complex data pipeline failures across all system layers; uses findings to drive pipeline improvements and communicates status, root cause, and resolution clearly to the team throughout the full lifecycle of an incident. • Assists with the development and delivery of data solutions, including data pipelines, API integration, and other structures and processes to support the data platform • Identifies, designs, and implements internal process improvements, including the automation of manual processes, optimization of data delivery, and refactoring of code for improved performance • Builds pipelines to enable the optimal extraction, transformation, and loading of data from a wide variety of data sources • Provides strategic assistance to BI leadership and the BI team by making recommendations in the areas of data management and best practices • Collaborates with developers, database administrators, data architects, and others on reporting and data management projects as needed • Takes on other duties needed to help drive our Purpose, fulfill our Brand Principles, and abide by our Organization’s Values

Role Description The Principal Data Architect is a key position within the Data Management team, responsible for the design, development, test, and implementation of best-in-class Data Integration solutions using MuleSoft, Azure, Java, Automation tools like Ansible, Terraform etc for the organization. This architecture role will be engaged in all phases of the Data Integration lifecycle and will be called upon to mentor less experienced team members as necessary. - Design, develop and maintain data solutions using best practices. - Architect complex data integration solutions using modern practices like APIs, messaging buses, and event streaming platforms to connect disparate data sources. - Develop a long-term, reliable vision and roadmap for how data will be collected, stored, managed, and utilized across the entire organization to achieve business objectives. - Define and implement policies, procedures, and standards for data quality, consistency, security, and compliance (e.g., GDPR, HIPAA). - Lead the creation of conceptual, logical, and physical data models to illustrate how data elements relate to each other and guide database design. - Research, evaluate, and recommend appropriate data technologies, tools, and platforms (cloud-based or on-premise) that align with business needs and future scalability requirements. - Continuously monitor and optimize existing data infrastructure for performance, security, and cost-efficiency. - Design and implement robust CI/CD pipelines to automate the building, testing, and deployment of data solutions, including automating infrastructure provisioning using Infrastructure as Code (IaC). - Provide architectural analysis for data integrations including definition of standards for scalability, security, error handling, and auditing. - Lead the design and evolution of hybrid infrastructure, blending cloud and on-premise systems into a unified, scalable, and reliable data platform. - Define and enforce data governance policies and security controls across all data and infrastructure, ensuring compliance with privacy regulations. - Building data ingestion and integration pipelines using tools like Apache Kafka or ETL technologies. - Assist in estimating and scoping of all data integration-related implementations. - Act as an agent of change, fostering a culture of cross-functional collaboration between data, development, and operations teams. - Design and build API security standards using Noname/Akamai. - Integrate different security solutions like Checkmarx using Azure CICD. - Analyze the requirements and prepare technical specifications and detail level design documents. - Drive the Design, Development & Deployment of data flows. - Implement DevOps Best practices for all data integrations, participate in all types of testing, including unit testing, point-to-point testing, end-to-end testing & UAT. - Support/enhance/create integrations to address business requirements, ensuring all related processes meet best-in-class standards offering high performance. - Designing, prototyping, and delivering API integration and applications in varied deployment models - cloud based, on-premise, and hybrid. - Build continuous improvement process for complex data systems, tools & reports. - Serves as resource to internal, offshore team & third-party team members on escalated issues, analyzing and designing specifications for less experienced team members. - Pursues self-development and effective relationships with others by sharing resources, information, and knowledge with coworkers and customers. Seeks opportunities to deliver continuous process improvement. - Serves as a resource to internal, offshore MuleSoft & onsite Dev Platform engineering teams and third-party team members on escalated issues and analyzing & designing specifications for less experienced team members. Will supervise 2 employees (Advanced Dev Ops Engineers). Qualifications - 3 or 4 year Bachelor's degree in Computer Science, Engineering, Math, Computer Information Systems or a related field of study plus 7 years of experience in a related occupation. Employer will accept any suitable combination of education, training and/or experience. - 7 years of experience with MuleSoft platform architecture and development. - 6 years of experience with IBM Integration Bus development and MQ Development. - 6 years of experience with Java development, Kafka and ETL. - 6 years of experience with Site Reliability Engineering and Infra as a code. - 6 years of experience with CheckMarx, Noname and API Security. - 5 years of experience with Kubernetes and OpenShift and Infra as a service. - 5 years of experience with Okta OR PING. - 5 years of experience with API gateway. - 3 years of experience with Azure CICD, Hashicorp OR Delinea Secrets. Compensation The salary for this role is $202,779.00, along with eligibility to earn an annual bonus.