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Senior Data Engineer – Automation, Analytics and AI
HybridFull-timeData EngineeringPharmaceuticalsBiotechnology
A life sciences company is seeking a Senior Data Engineer to design and deliver scalable data pipelines, automation, analytics, and AI-enabled solutions. The role is based in Hod HaSharon, Israel, follows a hybrid work arrangement, and includes up to 10–20% travel.
Responsibilities
- Design, develop, and maintain end-to-end data pipelines.
- Build automation processes, analytics products, dashboards, and AI-enabled solutions.
- Translate business needs into scalable and reliable technology solutions.
- Lead data, automation, analytics, and AI initiatives that improve operational efficiency and decision-making.
- Coordinate technical and business stakeholders across functions and locations.
- Plan and deliver projects, manage risks and issues, and prioritize work in a fast-paced environment.
- Support change adoption through stakeholder engagement and training.
Requirements
- Bachelor’s degree in science, computer science, engineering, mathematics, statistics, or a related field.
- At least 5 years of relevant hands-on experience for the senior position.
- Experience designing and delivering end-to-end data pipelines and analytics solutions.
- Demonstrated delivery of automation, analytics, AI/ML, dashboards, workflow automation, or ETL solutions with measurable improvements.
- Hands-on project management and cross-functional stakeholder coordination in a matrix environment.
- Proficiency in Python, data modeling, data pipelines, ETL tools, business process modeling, process mapping, and solution design.
- Knowledge of program and project planning, prioritization, risk and issue management, and Agile or Lean practices.
- Fluent English communication skills and the ability to present technical topics to non-technical audiences.
- Ability to support stakeholder engagement, training, change enablement, and solution adoption.
Nice to have
- Experience working across multiple countries or in regional programs.
- Exposure to integrations with IT and data science teams.
- Experience coordinating vendors.