Senior Data Engineer

Role Summary

Senior Data Engineer responsible for designing and operating enterprise-grade data pipelines powering analytics and AI for manufacturing and quality. Based in Thousand Oaks, CA, reporting to the Head of Data Digital & Technology, DD&T, and partnering with site teams and global DD&T colleagues. Lead cross-functional initiatives to standardize data ingestion and modeling, ensure data quality and governance, and deploy secure, scalable solutions while mentoring engineers and driving globally aligned practices.

Responsibilities

• Design and optimize data pipelines: ETL/ELT, batch/stream using Databricks and Dataiku, with strong observability and reliability.
• Develop reusable ingestion and transformation patterns to standardize processes and minimize redundant work across sites.
• Create and maintain modular data models (e.g., lakehouse/medallion) and semantic layers aligned with global architecture standards.
• Ensure data quality and compliance by implementing validation controls, governance frameworks, and audit-ready practices for regulated environments.
• Deploy and operate data services in cloud environments (AWS/Azure) using CI/CD, IaC, and DataOps best practices for performance and scalability.
• Collaborate with stakeholders—including product owners, data scientists, and global teams—to translate requirements into robust engineering solutions.
• Document and share technical designs and best practices, contributing to engineering standards and promoting reusability across programs.
• Provide technical leadership and mentorship, guiding engineers, reviewing designs/code, and influencing global best practices.

Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or related field, or equivalent experience in data engineering/digital product development.
• Technical Skills:
  • In-depth programming in Python, Java, or Scala.
  • Experience with data modeling, big data technologies (e.g., Hadoop, Spark), and database systems (SQL/NoSQL).
  • Familiarity with data warehousing and cloud platforms (AWS/Azure).
• Certifications: AWS Data Engineering or Cloud certification (preferred AWS Certified Data Engineer / Architect Associate; Databricks Certified Data Engineer Professional).
• Tools & Frameworks: Hands-on experience with Dataiku and/or Databricks; knowledge of CI/CD and Agile/SAFe practices.
• Other: Strong analytical/problem-solving skills, proficiency in data visualization, and ability to work in multi-stakeholder, agile environments with a collaborative, professional attitude.

Skills

• Data pipeline design and optimization
• Data modeling and semantic layers
• Data quality and governance
• Cloud platforms (AWS/Azure) and DataOps
• CI/CD, IaC, Dataiku, Databricks
• Collaboration with cross-functional teams
• Technical leadership and mentorship

Education

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or related field, or equivalent experience.