• Lead the design and delivery of enterprise AI applications, copilots, assistants, and agentic solutions. • Define implementation strategies that align AI capabilities with business objectives and user needs. • Guide teams in building scalable AI workflows, retrieval systems, orchestration layers, and tool-integrated experiences. • Drive best practices across prompt engineering, retrieval-augmented generation (RAG), tool calling, context management, testing, observability, and evaluation. • Partner with clients to understand business challenges and identify AI-powered opportunities. • Translate ambiguous requirements into practical implementation approaches and technical roadmaps. • Act as a trusted advisor during workshops, discovery sessions, and executive presentations. • Collaborate closely with Data Scientists, Data Engineers, Architects, Analytics Engineers, Product teams, and business stakeholders.

• Write production-level Python and SQL code, with a strong emphasis on complex SQL for data transformation, pipeline logic, and analytical query optimization. • Leverage AI tools and large language models to augment engineering workflows — from code generation and query optimization to automated testing, documentation, and process improvement. • Utilize AWS services such as Lambda, Glue, and Fargate for scalable data operations. • Build and maintain large-scale data pipelines using Apache Airflow. • Oversee the maintenance of Extract, Load, and Transform (ELT) processes using DBT. • Design optimized database schemas in PostgreSQL and Amazon Redshift to ensure data integrity and high performance. • Identify opportunities to apply AI-driven automation to repetitive or high-volume data engineering tasks, reducing manual effort and improving throughput.

• Conduct 60-minute technical interviews for Senior Data Engineer candidates. • Evaluate candidates' hands-on experience across modern data platforms and cloud-based data architectures. • Assess technical depth, engineering best practices, problem-solving ability, and real-world project experience. • Explore candidates' previous projects through detailed technical discussions and follow-up questions. • Evaluate knowledge of data engineering principles, cloud architecture, scalability, security, governance, and performance optimization. • Assess candidates' understanding of data lakes, lakehouses, data warehouses, and modern analytics platforms. • Assess communication skills and the ability to explain complex technical concepts clearly. • Complete structured interview scorecards and provide hiring recommendations after each interview. • Collaborate with recruiters to ensure consistent evaluation standards. • Contribute to improving interview questions and technical assessment processes when needed.

Role Description We're looking for a new rinder to join our team at rindus, where you will: - Design and evolve scalable event-driven architectures - Define Kafka topic strategies, partitioning models, schema governance, retention concepts, and operational best practices - Build reliable real-time data pipelines using Kafka - Improve data reliability, observability, performance, and cost efficiency across the platform - Drive engineering standards around data modeling, CI/CD, testing, and infrastructure automation - Support the migration from legacy integrations toward modern event-driven and cloud-native architectures - Mentor on and contribute to architectural and technical decisions - Continuously evaluate and introduce technologies that improve scalability and developer productivity - Work in an agile, product-driven team setup - Maintain close contact with IT colleagues to understand the needs and requirements of a high-performance, secure, and stable platform operation Qualifications - Minimum 3 years of professional experience as a Data Engineer or in a similar role - Deep practical knowledge of Kafka and event-driven architecture design - Experience operating Kafka in production - Solid understanding of data modeling, data integration, and scalable processing concepts - Familiarity with cloud platforms and infrastructure automation (AWS, Azure, or GCP) - Beneficial: Experience with Enterprise Service Bus technologies such as Qlik Talend or SAP S4 / BTP - A firm understanding and practical experience in tools and processes to ensure software quality, such as Unit Tests, TDD, and Test Automation - Strong communication and collaboration skills in cross-functional teams - Very good English language proficiency; good German language skills are a plus Requirements - Tech background with a growth mindset - Strong self-motivation and passion for the job - Willingness to learn new technologies Benefits - Being part of a dynamic and highly motivated international multicultural team of skilled professionals - Competitive compensation package (restaurants, transport, and childcare) - Flexible working model: remote - 23 holiday days - Flexible schedules with core working hours - DKV private health insurance from day 1 - Gym Sponsorship - English and German language classes - A young and ambitious team that knows when to work and when to have fun (Pizza day, Summer event, Málaga Tech Games, etc.)