About The Job
IOMED Data Engineering Team is responsible for building and maintaining optimized and highly available data pipelines that facilitate information extraction and transformation for our main products and internal applications. The core of your role will be designing, architecting, implementing, and testing data extraction and transformation tools in a microservices environment:
- Data processing pipelines
- Data model transformations
- Components of a multi-modal distributed database.
You will collaborate with the rest of the Data Engineering team in analyzing and understanding data sources, participating in the design, and providing insights and guidance on database technology and data modeling best practices.
This role should work closely with the Business Development and Data Science teams, gathering technical requirements for data governance and data quality across the company.
IOMED is a leading technology start-up company in the field of massive medical data extraction and processing. It is made up of a united, young, dynamic, and flexible team, which, after several years of working together, is characterized by its agility, enjoyment of work, and rapport. Accordingly, we are looking for candidates with the desire to innovate, launch a relevant project, and grow with it, always enjoying teamwork and challenges, which are many, every day.
As an employer, we offer equal opportunity. We want to grow our team with talented, dynamic people who want to make their mark in the field of AI and research, regardless of race, color, religion, national origin, gender, physical disability, or age.
What We Expect You To Do
You will have to feel comfortable giving support to the rest of the team and you can definitely expect to:
- Query, model and deploy with PostgreSQL, Redis, RabbitMQ.
- ETL with SQL and Python
- Design, implement & test microservices.
- Integrate our products with external APIs.
- Development and testing of our core products and frameworks.
- Be comfortable with container development with Docker.
- Testing, logging, measuring and alerting of the deployed services.
- Monitor the existing metrics, analyze data, and collaborate with other teams in an effort to identify and implement a system and process improvements.
- Ensure that the collected data is of high quality and optimal for use across the team and the business at large
- Oversee activities of the junior data engineering teams, ensuring proper execution of their duties and alignment with business vision and objectives
What We Expect From You.
- At least 8 years of working experience working in a data engineering department, preferably as a Data Engineer in a fast-paced environment and complex business
- Setting and a demonstrated experience in building and maintaining reliable and scalable ETL.
- Experience in data warehousing inclusive of dimensional modeling concepts and demonstrate proficiency in programming (SQL and Python will be your main tools of the trade).
- Proven skills of putting microservices to use, and you’re comfortable with working with containers in a cluster architecture.
- Work well in a team, can teach & learn from others, and communicate what you’re working on with non-technical team members.
You will be working in a very dynamic environment, which means that you must have a strong problem-solving ability, organization skills, and be proactive.
In terms of personality, we are looking for someone who enjoys working in a wide range of areas and adapts quickly to new situations.
What We Offer
- Competitive Salary.
- Permanent contract.
- Company profit-sharing scheme valued at up to €15,000 per year.
- Flexible remuneration with restaurant tickets, transport tickets, nursery, training, and medical insurance.
- Hybrid teleworking model and flexible schedule.
- 28 days of vacations per year.
- A warm, transparent and supportive team, with a huge emphasis on work-life balance.
- The opportunity to make your mark in e-health and AI.
What We Do
Our Healthcare Data Activation technology unlocks data from both structured and unstructured sources, including human-written records, thanks to our Natural Language Processing System. This data is standardized into OMOP Common Data Model, and never leaves hospitals' in-house systems, thanks to our Federated Data Model , enabling healthcare organizations to have activated and readily usable data while maintaining its protection and security.