BioSpace
Senior Data Engineer
Location: Thousand Oaks, CA
Compensation: $111,800.00 - $175,670.00 (U.S. base salary)
Responsibilities
Design and optimize data pipelines (ETL/ELT, batch/stream) using DD&T platforms like Databricks and Dataiku, ensuring 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.
Minimum Requirements / 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.
EEO Statement Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.
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Compensation: $111,800.00 - $175,670.00 (U.S. base salary)
Responsibilities
Design and optimize data pipelines (ETL/ELT, batch/stream) using DD&T platforms like Databricks and Dataiku, ensuring 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.
Minimum Requirements / 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.
EEO Statement Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.
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