דרושים » דאטה » Data Engineer

Medison offers hope to patients suffering from rare and severe diseases by forming partnerships with emerging biotech companies to accelerate access to highly innovative therapies in international markets. As the creator and leader of the global partnership category in the pharma industry, we strive to be Always Ahead and work relentlessly to bring therapy to patients in need, no matter where they live. Our values are at the core of every action we take, and we are committed to going above and beyond to benefit the patients we serve. We are a dynamic, fast-paced company operating in over 34 countries on 5 continents. We are looking for out-of-the-box thinkers, people who are passionate, caring, agile, and adaptive, to join us on our mission. If you are looking to make a difference in people's lives, we invite you to join us! Medison is seeking a Product Manager to be responsible for the full commercial management of product portfolios, including strategy development, budgeting, business planning, and performance monitoring to ensure target achievement. The Product Manager works closely with cross-functional teams across Medison and with international partners, leveraging an in-depth understanding of the therapeutic area and key opinion leaders (KOLs). The role combines field-based and office-based activities and requires cross-country and international travel as needed.

Responsibilities:

* Build and execute strategic business and marketing plans.
* Manage partnerships with suppliers and stakeholders, including meeting preparation, presentations, documentation, and follow-up.
* Implement marketing objectives, policies, and sales and marketing programs to maximize business performance.
* Develop and manage budget plans, with ongoing monitoring and control of expenses.
* Analyze sales reports and market data to identify trends, evaluate performance, and adjust strategies accordingly.
* Develop marketing materials, both digital and print, and obtain all required approvals in accordance with internal and supplier requirements.
* Collaborate cross-functionally with the Business Unit Head, Medical Manager, Aesthetics Team Leader, Sales teams, and external service providers to support product-related activities and administrative requirements.
* Independently manage and interpret scientific materials, share knowledge, and provide support to internal teams.
* Participate in business meetings with international partners, training sessions, conferences, and other professional events.
* Attend and represent the company at local and international conferences and industry events.
* Consistently uphold the highest standards of professionalism, integrity, ethics, and compliance, adhering to the Global Code of Business Conduct and related policies and procedures.
* Provide comprehensive support to sales teams, creating platforms and opportunities for sales initiatives, business growth, and market expansion.

City:
Petah Tikva

We are looking for a strong, hands-on Data Engineer to join our team and play a key role in building our data infrastructure from the ground up. In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases. You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption. This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.
What will your job look like?
Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
Design and implement scalable, flexible data architectures to support evolving business needs.
Build and manage data platforms, including data lakes and data warehouses.
Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.

We seek an experienced Senior Staff Data Engineer to join our AI and Data Solutions unit and champion an AI-first strategy. You will spearhead the development of Data Lakehouse processes, model core product domains, and define data engineering best practices across the organization. Serving as a technical project lead, you will provide strong direction and collaborate with Data Science, Analytics, R&D, and IT teams to elevate onboarding workflows. This role demands a proactive approach to optimizing system capabilities and driving cross-functional data initiatives.
Key Responsibilities:
Own the design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems.
Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT.
Apply advanced data modelling techniques to structure complex data assets into optimized facts, dimensions, and partitions.
Partner with cross-functional leadership across data science, analytics, R&D, and IT to identify requirements and improve workflows.
Orchestrate complex data workflows combining tools like Airflow and DBT with advanced Gen-AI development workflows using CloudCode.
Define, document, and popularize data engineering best practices, design patterns, and data quality standards across the unit.
Evaluate and implement modern data technologies spanning vendor-specific and open-source landscapes including GCP, AWS, and Apache Iceberg.
Provide technical direction and hands-on guidance to ensure high-performance execution, reliable pipeline delivery, and proactive problem-solving.

We are seeking an exceptional Product Manager that will own customer engagements end to end, from the first discovery call to production. You sit between the customer and our AI and software engineers, turning business and customer needs into a scoped plan, a spec engineers can build from, and evals that proves it works.
You're fluent in AI tools (Claude code/ codex/ etc.) to research faster, draft specs, prototype, and pressure-test ideas, and you have a real feel for what today's models can and can't do.
What you'll do:
Define and communicate a compelling product strategy, and roadmap across multiple domains and client engagements.
Own customer engagements end to end, from discovery through design, development, launch, and improvement.
Partner with engineering, design, data science, and delivery teams to ensure products meet high standards of usability, scalability, and technical integrity.
Translate market trends, customer insights, and business objectives into clear product requirements and measurable outcomes.
Manage product prioritization and release planning across competing client and business needs.
Participate in presales activities, including scoping, solution design, and client-facing presentations, to help shape proposals and ensure alignment between client needs and product vision.
Engage directly with clients and executives to define product vision, success metrics, and product roadmap.
Drive innovation and continuous improvement through experimentation, data-driven decisions, and a strong understanding of emerging AI capabilities and their limits.

our company seeks an experienced Senior Staff Data Engineer to join our AI and Data Solutions unit and champion an AI-first strategy. You will spearhead the development of Data Lakehouse processes, model core product domains, and define data engineering best practices across the organization. Serving as a technical project lead, you will provide strong direction and collaborate with Data Science, Analytics, R&D, and IT teams to elevate onboarding workflows. This role demands a proactive approach to optimizing system capabilities and driving cross-functional data initiatives.
Key Responsibilities
Own the design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems.
Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT.
Apply advanced data modelling techniques to structure complex data assets into optimized facts, dimensions, and partitions.
Partner with cross-functional leadership across data science, analytics, R&D, and IT to identify requirements and improve workflows.
Orchestrate complex data workflows combining tools like Airflow and DBT with advanced Gen-AI development workflows using CloudCode.
Define, document, and popularize data engineering best practices, design patterns, and data quality standards across the unit.
Evaluate and implement modern data technologies spanning vendor-specific and open-source landscapes including GCP, AWS, and Apache Iceberg.
Provide technical direction and hands-on guidance to ensure high-performance execution, reliable pipeline delivery, and proactive problem-solving.

We seek an experienced Senior Staff Data Engineer to join our AI and Data Solutions unit and champion an AI-first strategy. You will spearhead the development of Data Lakehouse processes, model core product domains, and define data engineering best practices across the organization. Serving as a technical project lead, you will provide strong direction and collaborate with Data Science, Analytics, R&D, and IT teams to elevate onboarding workflows. This role demands a proactive approach to optimizing system capabilities and driving cross-functional data initiatives.
Key Responsibilities:
Own the design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems.
Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT.
Apply advanced data modelling techniques to structure complex data assets into optimized facts, dimensions, and partitions.
Partner with cross-functional leadership across data science, analytics, R&D, and IT to identify requirements and improve workflows.
Orchestrate complex data workflows combining tools like Airflow and DBT with advanced Gen-AI development workflows using CloudCode.
Define, document, and popularize data engineering best practices, design patterns, and data quality standards across the unit.
Evaluate and implement modern data technologies spanning vendor-specific and open-source landscapes including GCP, AWS, and Apache Iceberg.
Provide technical direction and hands-on guidance to ensure high-performance execution, reliable pipeline delivery, and proactive problem-solving.

We're looking for a Data Engineer to own our data architecture end-to-end. You'll design, build, and scale the pipelines that power every pricing decision we make - from raw ingestion through our data lake to the analytics and BI layers our customers rely on. This is a hands-on leadership role: you'll set technical direction, drive architectural decisions, and mentor a team of data engineers, while still writing code and owning delivery.
What You'll Do:
Architect and build large-scale batch and streaming ETL/ELT pipelines
Own data lake design, table modeling, and partitioning strategy across billion-row datasets
Drive query performance and cloud cost optimization across AWS and GCP
Establish data quality, observability, and reliability standards - freshness, correctness, and SLAs
Partner with backend, product, and data science teams to expose data through internal and customer-facing APIs
Our Stack
Spark / EMR Airflow BigQuery PostgreSQL & Aurora Kafka RabbitMQ Elasticsearch Go Python AWS GCP Kubernetes Terraform.

We are looking for a highly skilled Data Engineer to join our growing Data Analytics Department.
As a Data Engineer in a multi cloud company, you will build data-driven solutions for our customers using cutting-edge data tools and large-scale data on AWS\GCP\Azure.
Job Responsibilities:
Lead data solutions design and development for our various clients and projects.
Design the solution by understanding the needs, modeling the data, choosing the right tools and defining the interfaces/dashboards.
Develop Data Pipelines, Data Lakes, DWHs, AI\ML models, Dashboards and reports using advanced tools and leading technologies.