Data Engineer

About The Job

The Data Platform team is responsible for running and maintaining the infrastructure in charge of managing large volumes of data in the healthcare environment. As a Data Engineer, you will have a passion for databases and data processes and will play a pivotal role in achieving our business objectives. Your primary responsibility will be to help the team build and maintain a scalable, secure, and reliable data platform that can accommodate the growing volume of data we manage. You will also collaborate with other teams to ensure that the data platform integrates smoothly with our data-driven applications and services.

About You

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, adapts quickly to new situations and don’t be afraid to step out of comfort zone.

Tareas

Task

You will have to feel comfortable giving support to the rest of the team and you can definitely expect to:

• Maintain, deploy and monitor the applications that make up our data platform, including both internally developed applications and those from third-party vendors.
• Monitor the existing metrics, analyze data and collaborate with other teams in an effort to identify and implement system and process improvements.
• Query, model and deploy with PostgreSQL.
• Support on database maintenance tasks, including: Monitor database grow & bloat contention, and backup monitoring, maintenance and test.
• Mentor and help the rest of the technical teams in the correct use of the tools/apps within the platform.
  
  

Requisitos

What We Are Looking For

• At least 3 years of working experience working in a data engineering department, preferably as a Data Engineer or Data Platform Engineer.
• Proven experience programming data driven applications or services (plpgsql 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 (we use Docker & Kubernetes & Helm).
• Knowledge of relational database modeling concepts and in query performance tuning, and desire to share knowledge with others.
• Having experience managing platforms or applications used for data discovery, data observability, federated governance, or data orchestration, like Airflow or Datahub, would be considered an advantageous asset.
• Excellent communication skills and ability to work in a team environment.
  
  

Beneficios

What We Offer

• Full-time permanent contract.
• Company profit-sharing scheme valued at up to €10,000 per year
• Flexible schedule, with the possibility of home office.
• 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.
  
  

About IOMED

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 Do

Nowadays, about 50% of clinical trials are delayed due to slow data collection from patients, which is done manually. As a result, clinical research is highly inefficient in both time and cost, taking years and billions of dollars to develop a new drug.

This problem could be solved through Real-World Data, that is, those contained in electronic medical records (EHRs). But unfortunately, up to 85% of existing clinical data is unstructured.

IOMED has found a solution to this situation, making it possible to fully harness the value of Real-World clinical data. We developed a tool that extracts the necessary data from clinical texts, resulting in a structured, standardized, and interoperable database that contains complete clinical information from hospitals.

In this way, non-reusable information is transformed into data available for Clinical Research, which allows increasing the number of patients that meet the criteria, as well as reducing the total time and manual work dedicated to this task.