For out client from pharmaceutical sector we are looking for Data Analyst.
What will you be doing?
- Designing databases and modeling data to support connection of new data sources.
- Profiling data from new sources and defining transformation rules.
- Checking quality of the data and investigating issues.
- Providing support in user acceptance testing of new deliverables.
- Creating detailed documentation of key data assets and transformation processes.
- Producing reports and presentation to deliver accurate information to the team.
- Contributing to process improvements, automation and standardization.
What is required to get the job done?
- Ability to build full understanding of our data and system components.
- 2+ years of experience in Data Analyst role.
- Solid experience in data analysis, profiling, integration and reporting.
- Very good knowledge about SQL (advanced level).
- Experience in database design and data modeling.
- Analytical and troubleshooting skills.
- Strong focus on details.
- Ability to explain complex problems in easy-to-understand way.
Nice to have:
- Experience with Big Data technologies.
- Knowledge of Java or Scala.
- Previous experience with healthcare/pharmaceutical data.
What are we building?
- Data platform to integrate, manage and curate complex medical data sets.
- ETL solutions to process data from multiple disparate sources (spanning different countries, languages and compliance requirements).
- Master data management tool specialized on the governance of electronic medical records (EMR) reference dimensions (diagnosis, posology, laboratory & test values, doctors, products).
- Privacy Hub that ensures patient data anonymization according to EU regulations.
- Business Intelligence solutions at the top of data we managed .
What technology are we using?
- Data Engineering: Cloudera Data Platform, Databricks, Hadoop, Hive, Kudu, Spark, Kafka, Camunda, Scala, Java.
- Web application development: Java, C#, Angular, Oracle, Elasticsearch, Kafka.
- Testing: Python, Robot Framework.
- Cloud: Microsoft Azure.
- Containerization: Docker, Kubernetes.