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Data & Integration Engineer(m/w/x)
Building and maintaining scalable data pipelines for AI/ML use cases in pharmaceutical research. Proficiency with Apache ecosystem, AWS data services, and Snowflake expected. Additional days off, subsidized staff restaurant.
Anforderungen
- Bachelor's/Master's degree in Computer Science, Engineering, related field, or equivalent proven experience as Data Engineer, Software Developer, or similar role
- Proficiency with Apache ecosystem (Spark, Parquet, Iceberg, Kafka, Airflow)
- Advanced SQL expertise for data modeling, optimized queries, and performance improvement
- Hands-on experience with AWS data services (Kinesis, Glue, Appflow, Lambda, S3)
- Hands-on experience with Snowflake
- Hands-on experience with dbt (dbt labs) for data pipelines
- Strong analytical skills with unstructured datasets
- Excellent English written and verbal communication skills
Aufgaben
- Design scalable data pipelines
- Develop scalable data pipelines
- Maintain scalable data pipelines
- Design ETL processes
- Develop ETL processes
- Maintain ETL processes
- Collaborate with data architects and modelers
- Collaborate with IT team members
- Define cloud-based data architecture strategy
- Evolve cloud-based data architecture strategy
- Optimize data storage solutions
- Manage data storage solutions
- Optimize data integrations (e.g., S3, Snowflake, dbt, Snaplogic)
- Manage data integrations (e.g., S3, Snowflake, dbt, Snaplogic)
- Ensure data quality, integrity, security, and accessibility
- Utilize AWS cloud services for data engineering workflows
- Monitor data pipelines for performance
- Optimize data pipelines for performance
- Monitor data pipelines for scalability
- Optimize data pipelines for scalability
- Monitor data pipelines for cost efficiency
- Optimize data pipelines for cost efficiency
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Spark
- Parquet
- Iceberg
- Kafka
- Airflow
- SQL
- Kinesis
- Glue
- Appflow
- Lambda
- S3
- Snowflake
- dbt
Benefits
Flexibles Arbeiten
- Home office
- Flexible working hours
Mehr Urlaubstage
- Additional days off
Gratis oder Vergünstigte Mahlzeiten
- Subsidized staff restaurant
- Vegetarian and vegan options
Weiterbildungsangebote
- Training and development opportunities
Gesundheits- & Fitnessangebote
- Health promotion programs
Öffi Tickets
- Public transport ticket
Noch nicht perfekt?
- Raiffeisen Bank InternationalVollzeitmit HomeofficeBerufserfahrenWienab 64.500 / Jahr
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Data & Integration Engineer(m/w/x)
Building and maintaining scalable data pipelines for AI/ML use cases in pharmaceutical research. Proficiency with Apache ecosystem, AWS data services, and Snowflake expected. Additional days off, subsidized staff restaurant.
Anforderungen
- Bachelor's/Master's degree in Computer Science, Engineering, related field, or equivalent proven experience as Data Engineer, Software Developer, or similar role
- Proficiency with Apache ecosystem (Spark, Parquet, Iceberg, Kafka, Airflow)
- Advanced SQL expertise for data modeling, optimized queries, and performance improvement
- Hands-on experience with AWS data services (Kinesis, Glue, Appflow, Lambda, S3)
- Hands-on experience with Snowflake
- Hands-on experience with dbt (dbt labs) for data pipelines
- Strong analytical skills with unstructured datasets
- Excellent English written and verbal communication skills
Aufgaben
- Design scalable data pipelines
- Develop scalable data pipelines
- Maintain scalable data pipelines
- Design ETL processes
- Develop ETL processes
- Maintain ETL processes
- Collaborate with data architects and modelers
- Collaborate with IT team members
- Define cloud-based data architecture strategy
- Evolve cloud-based data architecture strategy
- Optimize data storage solutions
- Manage data storage solutions
- Optimize data integrations (e.g., S3, Snowflake, dbt, Snaplogic)
- Manage data integrations (e.g., S3, Snowflake, dbt, Snaplogic)
- Ensure data quality, integrity, security, and accessibility
- Utilize AWS cloud services for data engineering workflows
- Monitor data pipelines for performance
- Optimize data pipelines for performance
- Monitor data pipelines for scalability
- Optimize data pipelines for scalability
- Monitor data pipelines for cost efficiency
- Optimize data pipelines for cost efficiency
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Spark
- Parquet
- Iceberg
- Kafka
- Airflow
- SQL
- Kinesis
- Glue
- Appflow
- Lambda
- S3
- Snowflake
- dbt
Benefits
Flexibles Arbeiten
- Home office
- Flexible working hours
Mehr Urlaubstage
- Additional days off
Gratis oder Vergünstigte Mahlzeiten
- Subsidized staff restaurant
- Vegetarian and vegan options
Weiterbildungsangebote
- Training and development opportunities
Gesundheits- & Fitnessangebote
- Health promotion programs
Öffi Tickets
- Public transport ticket
Über das Unternehmen
Boehringer Ingelheim
Branche
Pharmaceuticals
Beschreibung
The company is focused on delivering lasting value to patients through innovative therapies and early clinical development.
Noch nicht perfekt?
- Raiffeisen Bank International
Data Engineer for Corporate & Investment Banking(m/w/x)
Vollzeitmit HomeofficeBerufserfahrenWienab 64.500 / Jahr - Raiffeisen Bank International
Data Engineer for Corporate & Investment Banking(m/w/x)
Vollzeitmit HomeofficeBerufserfahrenWienab 64.500 / Jahr - Capgemini
(Senior) Data Engineer (Databricks/Snowflake)(m/w/x)
Vollzeitmit HomeofficeBerufserfahrenWien, Grazab 60.000 / Jahr - paiqo GmbH
Azure Data Engineer II - Agentic AI Platform(m/w/x)
Vollzeitmit HomeofficeBerufserfahrenWien