Data Engineer
Summary
A Data Engineer at Quantori builds data pipelines for a Life Science project, using Azure cloud, Databricks, Spark, and other tools to process structured and unstructured data for predictive modeling.
At Quantori we are seeking a Data Engineer for an ongoing Life Science project to be engaged in building data pipelines and leveraging cloud technologies.
Es esencial asegurarse de que cumple con los requisitos como solicitante para este puesto; por favor, lea atentamente la información a continuación.
The team works in the Central European Time.
Responsibilities:
Data organization and analysis: handling structured, semi-structured, unstructured, and image-based data.
Building data systems and pipelines
Preparing data for prescriptive and predictive modeling
Designing end-to-end pipelines within a hybrid big data architecture, using Cloud Native Azure, Databricks, Spark, Scala, sbt, Airflow, Python, SQL, etc.
Leveraging Azure Cloud services for building data pipelines and ensuring effective monitoring
What we expect:
3+ years of relevant experience in the Data Engineering field
Expertise in Spark
Expertise in Databricks
Experience in working with Azure Cloud
Strong SQL skills
Experience with building Data lakes, Data warehouses, and ETL solutions
Understanding of data structures, data modeling, and software architecture
Analytic and problem solving skills
Nice to have: xqbhyrx
Expertise with Snowflake and related technologies (e.g. dbt)
Ability to write robust code with Scala
Proficiency with public clouds (AWS, GCP, Azure)
We offer:
Competitive compensation
Fully remote work
Flexible working hours
Continuous education, mentoring, and professional development programs
A team with an excellent tech expertise
Es esencial asegurarse de que cumple con los requisitos como solicitante para este puesto; por favor, lea atentamente la información a continuación.
The team works in the Central European Time.
Responsibilities:
Data organization and analysis: handling structured, semi-structured, unstructured, and image-based data.
Building data systems and pipelines
Preparing data for prescriptive and predictive modeling
Designing end-to-end pipelines within a hybrid big data architecture, using Cloud Native Azure, Databricks, Spark, Scala, sbt, Airflow, Python, SQL, etc.
Leveraging Azure Cloud services for building data pipelines and ensuring effective monitoring
What we expect:
3+ years of relevant experience in the Data Engineering field
Expertise in Spark
Expertise in Databricks
Experience in working with Azure Cloud
Strong SQL skills
Experience with building Data lakes, Data warehouses, and ETL solutions
Understanding of data structures, data modeling, and software architecture
Analytic and problem solving skills
Nice to have: xqbhyrx
Expertise with Snowflake and related technologies (e.g. dbt)
Ability to write robust code with Scala
Proficiency with public clouds (AWS, GCP, Azure)
We offer:
Competitive compensation
Fully remote work
Flexible working hours
Continuous education, mentoring, and professional development programs
A team with an excellent tech expertise