• Leverage your expertise to design and maintain data transformation pipelines • Manage databases and cloud infrastructure • Ensure data is accessible and efficiently processed • Focus on performance, scalability, and security for data systems • Collaborate closely with the product team to document business needs and transform them into clear, actionable technical requirements • Build and maintain scalable ELT pipelines for reliable data ingestion, transformation, and delivery • Design, optimize, and manage data models in Snowflake for performance, scalability, and clarity • Create and maintain DAGs to define pipeline tasks, dependencies, and schedules for automated workflows • Collaborate with DevOps to configure and manage AWS infrastructure supporting data storage, pipelines, and transformations • Monitor pipelines to resolve failures and improve stability and data quality • Document pipelines, DAGs, and models to support onboarding and knowledge sharing

• Own and operate our data warehouse, pipelines, and transformation layer • Design, build, and maintain scalable, reliable data pipelines that ingest data from across our platform and third-party sources, ensuring data is always available and trustworthy for downstream consumers • Partner with data scientists and analysts to deliver clean, well-documented datasets and optimize query performance so teams spend less time wrangling data and more time generating insights • Incrementally improve and modernize our existing data systems - you won't build everything from scratch, but you'll know how to assess what we have, prioritize what matters, and migrate thoughtfully • Implement data quality monitoring, alerting, and documentation practices that build trust across the organization

Job Description: Position Summary The Data Science intern will assist with AI adoption into our business practice. Collaborating with Formex Global Product Management and Marketing, this role will create a Virtual Assistant (Chatbot) for the ITW Formex website to automate website inquiry responses with accurate, consistent responses and increase website visitor dwell time. This job will interact with ITW teams in US Central, Shanghai China, and Taiwan time zones and will be a remote position. Key Responsibilities: - Develop an intelligent chatbot capable of responding to website inquiries using accurate, consistent, authorized information - Expand the chatbot’s capability by incorporating client’s evolving requirements - Launch the chatbot on http://itwformex.com in English and ideally on https://www.itwformex.com/zh-CN in Simplified Chinese Education and Skills: - Must be pursuing a Bachelor’s Degree in a quantitative discipline (Computer Science, Data Science, Data Engineering, Artificial Intelligence, Applied Mathematics, Statistics, or related) from an accredited university - Proficient experience in data science focused on data for client studies, modeling, data wrangling, and/or ML/AI - Fluency in Python, R, Java and other computing languages - Able to work directly with clients in complex analysis and presenting deliverables to non-technical personnel - Able to travel as necessary to meet project and client requirements - Must be able to work autonomously and be self-directed - Able to work within a collaborative team environment and coordinate activities between program components - Excellent communication skills, both written and verbal - Strong analytical skills, critical thinking, and attention to detail - Bilingual in Mandarin preferred Compensation Information: $25/hour ITW is an equal opportunity employer. We value our colleagues’ unique perspectives, experiences and ideas and create workplaces where everyone can develop their careers and perform to their full potential. As an equal employment opportunity employer, ITW is committed to equal employment opportunity and fair treatment for employees, beginning with the hiring process and continuing through all aspects of the employment relationship. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, national origin, age, disability, protected Veteran status or any other characteristic protected by applicable federal, state, or local laws.

• Provide strategic technical leadership in data engineering, serving as the primary customer-facing expert on DISN network topology data to enable advanced data correlation and enrichment. • Represent the team in high-level technical discussions and decision-making with internal and external stakeholders, influencing solution design and architecture. • Architect, design, develop, document, test, and deploy complex software solutions using Python, JavaScript, Java, and SQL, ensuring scalability and maintainability. • Lead the creation of advanced Kibana visualizations and dashboards, leveraging machine learning capabilities and React to deliver actionable insights. • Oversee the design and implementation of robust data enrichment pipelines, integrating diverse data sources into Confluent (Kafka) and Elastic platforms. • Direct the development and management of multi-site Kafka and Elastic clusters, including deployment, configuration, testing, troubleshooting, and maintenance to support mission-critical operations. • Lead Kafka system integrations between Elasticsearch/Logstash and other enterprise systems. • Guide Agile collaboration, leading scrum teams, mentoring junior engineers, and fostering a culture of continuous improvement and innovation. • Communicate and collaborate effectively with geographically distributed teams to ensure alignment and successful completion of project objectives. • Troubleshoot and resolve complex installation, infrastructure, and system issues; proactively report, monitor, and mitigate technical risks. • Author, review, and maintain comprehensive technical documentation, including DoD requirements, interface documents, and security compliance artifacts. • Ensure all solutions adhere to DoD security standards and guidelines, and provide oversight for platform sustainment and reliability, proactively addressing operational challenges.