• Designs and builds relational databases for data storage or processing • Develops strategies for warehouse implementation, data acquisition and access, and data archiving and recovery • Builds data models and defines the structure, attributes and nomenclature of data elements • Evaluates new data sources for adherence to the organization's quality standards and ease of integration • Provides subject matter expertise regarding information architecture • Develops and enforces the data architecture standards • Develops and maintains documentation that maps data models to information systems and business applications • Validates and fixes information management issues related to data quality framework (completeness, accuracy, availability, timeliness, consistency, etc.) • Manages data dictionary to improve documentation and coordination • Assists in building of enterprise architecture information blueprints and data models

• Lead the design and implementation of data and AI/ML architecture solutions across cloud and on-premise platforms. • Lead complex customer engagements, providing strategic technical vision and aligning solutions with customer business goals. • Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor. • Lead technical workshops, training sessions, and presentations. • Define and execute data lifecycle processes: ingestion, storage, processing, and visualization. • Collaborate with business units and stakeholders to align solutions with business goals. • Ensure solutions adhere to security, compliance, and architecture frameworks (e.g., AWS Well-Architected, GCP Architecture Framework). • Lead cross-functional teams, providing mentorship and guidance to technical talent. • Design and execute proofs of concept for emerging technologies like Generative AI, Machine Learning. • Drive backend/ML services best practices for scalable and maintainable solutions. • Oversee data governance and data quality processes across platforms. • Stay updated with the latest technology trends and continuously improve the architecture strategy.

• Act as the owner of the product roadmap and ensure the "why" behind every feature is clearly translated into technical requirements. • Masterfully structure engineering proposals, write high-quality technical tickets, and define clear acceptance criteria for developers and data scientists. • Lead daily progress meetings, run scrums, and manage sprints with precision to ensure engineering teams remain focused and bottlenecks are cleared immediately. • Directly oversee the integration of our products, ensuring they are implemented to automate complex tasks and improve manufacturing knowledge retrieval.

• Lead the hands-on technical implementation and deployment of Viaduct’s software solutions within large-scale enterprise environments. • Make critical data integration decisions and build robust connectors across a variety of data types and systems (SQL, NoSQL, APIs, etc.). • Create and support batch, incremental, and real-time data pipelines to ensure high-quality data ingestion from client systems. • Set up and deploy LLM and agentic systems in practice. You will be responsible for prompt engineering, performance testing, and iterating on agent behavior to ensure reliability and accuracy. • Establish and automate validation and cleaning processes to ensure data quality across various client integrations. • Work directly with customers across a variety of contexts to troubleshoot technical hurdles and ensure successful solution adoption.