Data Engineer

Quantori; España; Remote; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Fully remote work

Competitive compensation

Education and development programs

Job summary

Quantori is seeking a Data Engineer for an ongoing Life Science project, focused on building data pipelines and leveraging cloud technologies. The role supports end-to-end data workflows across structured, semi-structured, and image-based data in a modern hybrid big data environment.

You will work with Spark, Databricks, Azure, Python, SQL, and Airflow to design scalable pipelines, load data lakes and warehouses, and enable prescriptive and predictive modeling.

Qualifications

• 5+ years of experience in Data Engineering.
• Expertise in Spark.
• Expertise in Databricks.
• Experience with Azure Cloud.
• Experience with building Data lakes, Data warehouses, and ETL solutions.
• Understanding of data structures, data modeling, and software architecture.
• Analytic and problem solving skills.

Responsibilities

• Data organization and analysis across 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.
• Leveraging Azure Cloud services for building data pipelines and monitoring.

Skills

Data engineering

Spark

Databricks

Azure Cloud

Python

SQL

Airflow

Data modeling

Tools

Spark

Databricks

Azure Cloud

Airflow

Python

SQL

Scala

sbt

Snowflake

dbt

Job description

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.

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:

• 5+ years of relevant experience in the Data Engineering field
• Expertise in Spark
• Expertise in Databricks
• Experience in working with Azure Cloud
• 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:

• 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
• Continuous education, mentoring, and professional development programs