Senior Data Engineer

As a Sr. Data Engineer at Molex, you will be a vital contributor to our Enterprise Data Platform, responsible for designing and implementing data pipelines, optimizing data workflows, Managing Data Storage and ensuring data quality, reliability, and accessibility. Your work will be instrumental in empowering our organization to make data-driven decisions and fueling innovation across the company.

Joining our Enterprise Data Platform team means becoming a key player in a dynamic and innovative group of professionals dedicated to unlocking the power of data. Here, you'll find a diverse and collaborative environment where your ideas and expertise will shape the future of our data-driven organization. We pride ourselves on fostering a culture of continuous learning, creativity, and teamwork, and we're looking for individuals who are eager to contribute their skills and passion to our shared mission.

• Collaborate closely with business partners and data scientists to align data engineering efforts with their specific needs and objectives, ensuring that data solutions contribute effectively to the organization's overall goals.
• Develop, maintain, and optimize data pipelines using tools such as Snowflake, AWS Glue, and Lambda.
• Design and implement data modeling and ETL/ELT processes to ensure data quality, consistency, and availability.
• Design and Organize databases such as Snowflake, AWS DynamoDB, or AWS S3.
• Assembling large, complex sets of data that meet non-functional and functional business requirements.
• Write validation checks to catch errors, remove duplicates, and normalize formats so downstream teams trust the data.
• Monitor and troubleshoot data pipelines, resolving issues to ensure uninterrupted data flow.
• Optimize and fine-tune data pipelines for performance and efficiency.
• Manage and maintain data warehouses and ensure data security and compliance with company policies and relevant regulations.
• Perform data transformations, aggregations, and data cleansing to support analytics and reporting needs.
• Implement data integration strategies for streaming and batch data sources.
• Automate and orchestrate data workflows to improve efficiency and reduce manual intervention.
• Document data engineering processes, pipelines, and architecture for knowledge sharing and compliance.
• Stay up-to-date with industry best practices, emerging technologies, and trends in data engineering.

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 10-15+ proven years of experience as a Data Engineer or similar role, with a strong understanding of data engineering principles and best practices.
• Proficiency in SQL and data modeling.
• Experience with data warehouse technologies such as Snowflake.
• Strong programming skills in languages like Python, Java, or Scala.
• Familiarity with cloud computing platforms, particularly AWS.
• Understanding of data integration concepts and tools like AWS Glue and Lambda.
• Experience with Dev Ops practices and tools, such as continuous integration (CI) and continuous deployment (CD) pipelines, version control systems (e.g., Git).
• Experience in using Agile project management and collaboration tools (e.g., Jira, Confluence) to track progress and manage work in an Agile environment.
• Excellent problem-solving and troubleshooting skills.

• Certification in data engineering or related AWS certifications.
• Knowledge of data orchestration and workflow management tools.
• Knowledge of data governance and compliance best practices.
• Ability to mentor junior team members and lead data engineering projects.
• Strong project management and organizational skills.

Ability to collaborate closely with data scientists to deploy and…