Senior Data Engineer (AWS)
⚲ Kraków
24 000 - 32 000 PLN netto (B2B) | 20 300 - 27 100 PLN brutto (UoP)
Wymagania
- Python
- Spark
- AWS Glue
- SQL
- Databricks
Opis stanowiska
At Grape Up, we transform businesses by unlocking the potential of AI and data through innovative software solutions.
We partner with industry leaders, from the automotive and manufacturing industries, to build sophisticated Data & Analytics platforms that transform how organizations manage and leverage their data assets. As an AWS Partner, we frequently deliver solutions built on the AWS ecosystem, though our data engineers work across cloud platforms as project needs require. Our solutions provide comprehensive capabilities spanning data storage, management, advanced analytics, machine learning, and AI, enabling enterprises to accelerate innovation and make data-driven decisions.
Responsibilities
• Design and implement a scalable architecture capable of handling the high volume of Automotive and IoT data (e.g. telemetry, sensor, and simulation data)
• Build a flexible data preprocessing pipelines that are extensible and that can be integrated into customer’s existing platform
• Optimize and enhance system setup and improve data structures following industry best practices
• Collaborate effectively with data engineering team members while partnering closely with analytics and data science teams to meet user needs
• Collaborate with business stakeholders and technical teams to understand data requirements, translate business needs into technical solutions
Requirements
• Master’s degree in computer science, Data Engineering, AI, or a related field
• 5+ years of professional experience in Data Engineering and Big Data, building production-grade data platforms and pipelines
• Strong experience with Apache Spark (PySpark), including performance optimization, and large-scale data processing
• Proven experience with AWS data engineering stack (e.g., S3, Glue, Athena Amazon EMR)
• Proficiency in Python and SQL for data transformations and analytics workloads
• Experience with Infrastructure as Code (Terraform, CloudFormation)
• Experience with data pipeline orchestration
• Strong problem-solving skills and ability to work independently
• Fluency in English and Polish, both written and spoken
Nice to have
• Databricks experience (Unity Catalog, Delta Lake and Lakehouse architecture)
• Data Engineer certificate (AWS or Databricks)
• Experience processing high-volume Automotive or IoT data (e.g., telemetry, sensor, or event-based data)
• Experience with streaming tools like Kafka, Kinesis or similar
Benefits
• Non-corporate work environment among experienced engineers
• Individual growth & development plan supported by cyclical feedback sessions
• Access to knowledge platforms (e.g. Pluralsight)
• Equipment of your choice
• Financing of conferences, external trainings, and certifications
• Language lessons (English, German and Polish for foreigners)
• LuxMed private medical care
• Weekly Lunch & Learn where we meet up in the office, lunch together, and share our knowledge
• Employee referral program
• Rewards for the success of the month and year awarded by our employees
• Special rewards for your years with us (G-Man)
• Integration activities
We partner with industry leaders, from the automotive and manufacturing industries, to build sophisticated Data & Analytics platforms that transform how organizations manage and leverage their data assets. As an AWS Partner, we frequently deliver solutions built on the AWS ecosystem, though our data engineers work across cloud platforms as project needs require. Our solutions provide comprehensive capabilities spanning data storage, management, advanced analytics, machine learning, and AI, enabling enterprises to accelerate innovation and make data-driven decisions.
Responsibilities
• Design and implement a scalable architecture capable of handling the high volume of Automotive and IoT data (e.g. telemetry, sensor, and simulation data)
• Build a flexible data preprocessing pipelines that are extensible and that can be integrated into customer’s existing platform
• Optimize and enhance system setup and improve data structures following industry best practices
• Collaborate effectively with data engineering team members while partnering closely with analytics and data science teams to meet user needs
• Collaborate with business stakeholders and technical teams to understand data requirements, translate business needs into technical solutions
Requirements
• Master’s degree in computer science, Data Engineering, AI, or a related field
• 5+ years of professional experience in Data Engineering and Big Data, building production-grade data platforms and pipelines
• Strong experience with Apache Spark (PySpark), including performance optimization, and large-scale data processing
• Proven experience with AWS data engineering stack (e.g., S3, Glue, Athena Amazon EMR)
• Proficiency in Python and SQL for data transformations and analytics workloads
• Experience with Infrastructure as Code (Terraform, CloudFormation)
• Experience with data pipeline orchestration
• Strong problem-solving skills and ability to work independently
• Fluency in English and Polish, both written and spoken
Nice to have
• Databricks experience (Unity Catalog, Delta Lake and Lakehouse architecture)
• Data Engineer certificate (AWS or Databricks)
• Experience processing high-volume Automotive or IoT data (e.g., telemetry, sensor, or event-based data)
• Experience with streaming tools like Kafka, Kinesis or similar
Benefits
• Non-corporate work environment among experienced engineers
• Individual growth & development plan supported by cyclical feedback sessions
• Access to knowledge platforms (e.g. Pluralsight)
• Equipment of your choice
• Financing of conferences, external trainings, and certifications
• Language lessons (English, German and Polish for foreigners)
• LuxMed private medical care
• Weekly Lunch & Learn where we meet up in the office, lunch together, and share our knowledge
• Employee referral program
• Rewards for the success of the month and year awarded by our employees
• Special rewards for your years with us (G-Man)
• Integration activities
🔍 Dekoder Ogłoszenia
🔴
our data engineers work across cloud platforms as project needs require
Chociaż główny nacisk kładziony jest na AWS, mogą pojawić się projekty wymagające pracy z innymi chmurami, co może oznaczać potrzebę szybkiego uczenia się i adaptacji.
🔴
Build a flexible data preprocessing pipelines that are extensible and that can be integrated into customer’s existing platform
Może to oznaczać konieczność pracy z różnymi, często przestarzałymi lub słabo udokumentowanymi systemami klientów, co wymaga dużej elastyczności i umiejętności rozwiązywania problemów.
🟡
Collaborate effectively with data engineering team members while partnering closely with analytics and data science teams to meet user needs
Oznacza to częste interakcje z różnymi zespołami, co może wymagać doskonałych umiejętności komunikacyjnych i zdolności do tłumaczenia złożonych koncepcji technicznych na język zrozumiały dla innych.
🟡
Collaborate with business stakeholders and technical teams to understand data requirements, translate business needs into technical solutions
Wymaga to nie tylko umiejętności technicznych, ale także zdolności do rozumienia celów biznesowych i przekładania ich na konkretne rozwiązania techniczne, co może być wyzwaniem.