Data Engineer

AEVI; Berlin; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Benefits dieser Stelle

Quick integration into a highly motivated, global team

An open, flexible culture

Fun team and company-wide events

Space, time and tools for self-development

Career development guidance and opportunities

Zusammenfassung

AEVI, based in Berlin, is looking for a Data Engineer to work within the fintech industry, leveraging AWS technologies for cloud-based payment applications. The role involves translating business requirements into technical specifications, managing data architecture, and ensuring compliance with regulations.

Successful candidates will have strong expertise in AWS data solutions, be proficient in Python and Java, and possess excellent communication skills. AEVI offers a flexible working culture and opportunities for career development.

Qualifikationen

• Proficiency in streaming platforms (Kafka, AWS Kinesis) for real-time data processing.
• Deep knowledge of AWS Cloud Data technologies.
• Proficiency in AWS database services.
• Familiarity with infrastructure-as-code tools (Terraform, AWS CloudFormation).
• Good understanding of data classification, encryption, and privacy.
• Solid knowledge of Python and Java.
• Experience with big data frameworks (Apache Spark, Hadoop).
• Strong expertise in SQL, DML, and DDL.
• Strong data modeling and design skills.
• Excellent communication skills.

Aufgaben

• Translate business requirements into technical specifications for AEVI’s AWS-based data architecture.
• Work with technologies such as Aurora, Oracle, Athena, Glue, and QuickSight.
• Manage and optimize Data Warehouses & Data Lakes.
• Design, configure, and administer data architecture in compliance with PCI, GDPR, and CCPA.
• Document data flows and implement data models within business applications.
• Ensure cloud data management meets CIA (Confidentiality, Integrity, Availability) standards.
• Redesign data models to maintain regulatory compliance.
• Develop and manage a structured data access model.

Kenntnisse

Streaming platforms (Kafka, AWS Kinesis)

AWS Cloud Data technologies

AWS database services

Infrastructure-as-code tools (Terraform, AWS CloudFormation)

Data classification, encryption, and privacy

Python

Java

Big data frameworks (Apache Spark, Hadoop)

SQL, DML, and DDL

Data modeling and design

Jobbeschreibung

Responsibilities

• Want to work in the fintech industry, using the latest technologies and tools to help deliver online cloud and container based applications for a new breed of payment services?
• We are searching for Data Engineer, who will be responsible for transferring business requirements into technical requirements of the AEVI data architecture based on AWS technology
• Translate business requirements into technical specifications for AEVI’s AWS-based data architecture
• Work with technologies such as Aurora, Oracle, Athena, Glue, and QuickSight
• Manage and optimize Data Warehouses & Data Lakes
• Design, configure, and administer data architecture in compliance with PCI, GDPR, and CCPA
• Document data flows and implement data models within business applications
• Ensure cloud data management meets CIA (Confidentiality, Integrity, Availability) standards
• Redesign data models to maintain regulatory compliance
• Develop and manage a structured data access model

Benefits

• Quick integration into a highly motivated, global team
• An open, flexible culture allowing you to work in the way that works for you
• Fun team and company-wide events
• Space, time and tools for self-development
• Career development guidance and opportunities

Qualifications

• Proficiency in streaming platforms (Kafka, AWS Kinesis) for real-time data processing
• Deep knowledge of AWS Cloud Data technologies
• Proficiency in AWS database services
• Familiarity with infrastructure-as-code tools (Terraform, AWS CloudFormation)
• Good understanding of data classification, encryption, and privacy
• Solid knowledge of Python and Java
• Experience with big data frameworks (Apache Spark, Hadoop)
• Strong expertise in SQL, DML, and DDL
• Strong data modeling and design skills
• Excellent communication skills at both business and technical levels