11 часов назад
Principal Data Engineer (Biotech)
159 422 - 215 689$
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Principal Data Engineer (AWS/Python/PySpark): Leading the design and implementation of robust data architectures, cloud data platforms, pipelines, and integration solutions for a biotechnology organization with an accent on data governance, quality, security, compliance, and cloud cost optimization. Focus on architecting scalable data solutions, resolving complex data challenges, and mentoring a high-performing data engineering team.
Location: Thousand Oaks, California, United States
Annual salary: USD 159,422.60–215,689.40
Company
is a biotechnology company developing, manufacturing, and delivering medicines across oncology, inflammation, general medicine, and rare disease.
What you will do
- Lead the design, development, and implementation of the data strategy.
- Architect and oversee robust data platforms, architectures, pipelines, and integration solutions.
- Establish data governance policies and standards supporting data quality, security, and compliance.
- Manage cloud-based data solutions using AWS, Azure, GCP, or comparable platforms, including cost optimization.
- Identify and resolve complex data engineering challenges while translating business requirements into technical solutions.
- Mentor and lead a high-performing data engineering team and promote engineering best practices.
Requirements
- Experience using AWS, Azure, or GCP for data engineering solutions, with a strong understanding of cloud architecture and cost optimization.
- Professional experience with Python, PySpark, and SQL, including big-data ETL performance tuning.
- Proven ability to lead and develop high-performing data engineering teams.
- Strong analytical, troubleshooting, problem-solving, communication, presentation, and prioritization skills.
- Doctorate with 2 years, master’s degree with 4 years, bachelor’s degree with 6 years, associate’s degree with 10 years, or high school diploma/GED with 12 years of Data Engineer experience.
- Ability to work effectively with global, virtual teams.
Nice to have
- Experience with OLAP and OLTP data modeling and performance tuning.
- Experience with Apache Spark and Apache Airflow.
- Experience with Git or Subversion, CI/CD, automated unit testing, and DevOps.
- AWS Certified Data Engineer or Databricks certification.
Culture & Benefits
- Collaborative, innovative, and science-based work culture.
- Health, dental, vision, life, and disability insurance, plus flexible spending accounts.
- Retirement and savings plan with company contributions.
- Discretionary annual bonus program and stock-based long-term incentives.
- Award-winning time-off plans and career development opportunities.
- Flexible work models where applicable to the posted work location type.
Hiring process
- Applications are accepted until a sufficient number of candidates are received or a candidate is selected.
- Reasonable accommodation is available for candidates with disabilities.
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