• Building efficient, critical data pipelines and data platform • Collaborate closely with ML/AI Engineers, Backend Engineers and product to create the data sets that power vidIQ’s algorithms • Be an advocate for data quality, acquisition of new data sources, and data infrastructure tooling • Work closely with cross-functional teammates, including product managers, designers, backend, DevOps and ML/AI Engineers to deliver the highest impact to our users

• Provides expertise in designing, developing, and maintaining scalable data pipelines and architectures supporting enterprise data catalogs and federated data environments • Integrates structured and unstructured data from clinical, operational, and research systems (e.g., EHRs, data lakes, APIs) • Implements metadata harvesting, data lineage, and data quality enforcement aligned with enterprise governance frameworks • Supports AI/ML readiness through feature engineering, data transformation, and pipeline automation • Works within federal healthcare environments, ensuring compliance with HIPAA, DoD, and DHA data standards

• Design, implement, and maintain scalable data pipelines to collect, process, and store data from various sources. • Ensure data quality, accuracy, and consistency throughout the pipeline. • Design and implement existing data models for predictive analytics, machine learning, and data exploration. • Optimize data structures and storage to support predictive analytics/machine learning processes. • Work closely with cross-functional teams to integrate data from diverse sources, including databases, APIs, and external data providers. • Develop and maintain ETL processes to transform and enrich raw data into actionable insights. • Monitor and optimize the performance of data pipelines and databases to meet business requirements. • Stay up-to-date with the latest advancements in data engineering and data science technologies. • Share knowledge and mentor junior team members.

• Design, develop, and maintain scalable ETL (Extract, Transform, Load) pipelines to process large volumes of data from diverse sources. • Build and optimize data storage solutions, such as data lakes and data warehouses, to ensure efficient data retrieval and processing. • Integrate structured and unstructured data from various internal and external systems to create a unified view for analysis. • Ensure data accuracy, consistency, and completeness through rigorous validation, cleansing, and transformation processes. • Maintain comprehensive documentation for data processes, tools, and systems while promoting best practices for efficient workflows. • Collaborate with product managers, and other stakeholders to gather requirements and translate them into technical solutions. • Participate in requirement analysis sessions to understand business needs and user requirements. • Provide technical insights and recommendations during the requirements-gathering process. • Participate in Agile development processes, including sprint planning, daily stand-ups, and sprint reviews. • Work closely with Agile teams to deliver software solutions on time and within scope. • Adapt to changing priorities and requirements in a fast-paced Agile environment. • Conduct thorough testing and debugging to ensure the reliability, security, and performance of applications. • Write unit tests and validate the functionality of developed features and individual elements. • Writing integration tests to ensure different elements within a given application function as intended and meet desired requirements. • Identify and resolve software defects, code smells, and performance bottlenecks. • Stay updated with the latest technologies and trends in full-stack development. • Propose innovative solutions to improve the performance, security, scalability, and maintainability of applications. • Continuously seek opportunities to optimize and refactor existing codebase for better efficiency. • Stay up to date with cloud platforms such as AWS, Azure, or Google Cloud Platform. • Collaborate effectively with cross-functional teams, including testers, and product managers. • Foster a collaborative and inclusive work environment where ideas are shared and valued.