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 on 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 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.
You have at least 3 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. You have 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). You have proven skills of putting microservices to use, and you’re comfortable with working with containers in a cluster architecture. You work well in a team, can teach & learn from others, and communicate what you’re working on with non-technical team members.
Things You Might Do
IOMED is a startup, so you’ll have to be comfortable rolling up your sleeves and doing whatever needs doing. However, 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 system and process improvements.
- Ensure that the collected data is of a 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 offer
- Gross annual wage: 35.000€-40.000€.
- Full-time permanent contract
- Profit-sharing scheme.
- Flexi-time schedule, with possibility of home office once a week.
- A warm, transparent and supportive team, with huge emphasis on work-life balance.
- Most days, lunch together in our sunny terrace.
IOMED is a technological company of software development. It was launched in 2016, funded by local and international ventures.
We are passionate and talented young professionals, from all around Spain and the world (It couldn't be any other way, as we're based in beautiful and bright Barcelona). Our “dream team” is made up by mathematicians, statisticians, bioinformaticians and physicians.
As a startup, we are looking for people who are eager to innovate and be part of a project with impact on healthcare industry, enjoying what we do, team-work and taking on new challenges.
IOMED is an equal opportunity employer. We are still a small team and are committed to growing in an inclusive manner. We want to augment our team with talented, dynamic people irrespective of race, color, religion, national origin, sex, physical or mental disability, or age.
What we do
Nowadays, around 50% of Clinical Trials are delayed due to patient recruitment, since patient data collection is performed in a manual fashion. As a result, clinical research is highly inefficient both in time and cost, taking years and billions of dollars to develop a new drug.
This problem could be solved through Real World Data, i.e. derived from Electronic health records (EHR). But unfortunately up to 85% of existing clinical data is unstructured, i.e. in plain text. This also leads, in part, to the existence of data silos, making it impossible to aggregate data from different hospitals.
IOMED has found the solution to this situation, making it possible to take advantage of full value of clinical Real World Data. We developed a tool that extracts the necessary data from clinical texts, which results in a structured, standardized and interoperable database that contains the complete clinical information from hospitals.
By this means, non-reusable information is transformed into data available for Clinical Research, allowing an enormous increase in criteria-compliant patients and a reduction of total time and manual labor devoted to this task.