• Design, build, and maintain robust ETL/ELT data pipelines on Google Cloud Platform • Write efficient, production-grade SQL for data transformation, modeling, and analysis • Develop and maintain Python -based data processing scripts and automation • Build and manage workflow orchestration using Apache Airflow (e.g. Cloud Composer) • Work with Datastream and other GCP services to ingest and replicate data from source systems • Support and maintain data models and dashboards in Looker • Implement data quality checks, monitoring, and alerting for pipelines • Troubleshoot and resolve pipeline and data issues • Collaborate with analysts, data scientists, and business stakeholders to understand data needs • Document pipelines, data flows, and processes

• Assist in building and maintaining data pipelines that move and transform data across our systems • Write and optimize SQL queries to extract, clean, and prepare data for analysis • Develop Python scripts to automate data tasks and support ETL/ELT processes • Support the team in working with our cloud data platform (Google Cloud Platform) • Help monitor scheduled data workflows and troubleshoot basic issues • Contribute to data quality checks and documentation • Learn and grow into our full data stack with guidance from senior engineers

Your role at DynatraceAt Dynatrace, Data Engineering manages and transforms data into information for decisionmakers. This includes assessment, design, acquisition and/or implementation of tools, stores and pipelines for turning data into business value. We are seeking a Lead Software Engineer in Data who will provide key technical direction for and hands-on effort with a small team of data engineers supporting our Business Intelligence function. A core role will be directing and helping to implement transformative pipelines of business data into our Snowflake environment. The ideal candidate will have experience and demonstrable skill with in creating robust software infrastructure for data engineering applications, with expertise in Python, Snowflake, SQL and related technologies. The ideal candidate will have also demonstrated experience in mentoring and upskilling more junior members of the team. - Lead the design, implementation, and maintenance of scalable data pipelines in the Snowflake eco-system including third party vendor tools such as AWS, Fivetran, etc. - Key contributor to a Data Engineering strategy to ensure efficient data management for operations and enterprise analytics - Key technical expert for business stakeholder engagement on business data initiatives - Collaboration with colleagues in Data Modeling, BI and Data Governance teams for platform initiatives - Provide the technical interface to data engineering vendors - Ensure data engineering standards align with industry best practices for data governance, data quality, and data security - Evaluate and recommend new data technologies and tools to improve data engineering processes and outcomes What will help you succeed - Proven experience in a hands-on data engineering role, especially in relation to business operations data - Experience as a technical mentor for other data engineers - Bachelor’s degree in Computer Science, Information Systems or related field, or equivalent experience - Experience managing stakeholder engagement, collaborating across teams, and working on multiple simultaneous projects - A strong sense of curiosity, engagement in continuous learning and self improvement, and a knowledge of the trends in the data industry - Hands-on experience implementing robust, scalable data pipelines - Extensive experience acquiring data from REST APIs - Experience in Python and software engineering, with the ability to write efficient, maintainable, and scalable data pipeline code - Understanding of testing and profiling in the context of data infrastructure, including unit testing, integration testing, profiling code - Knowledge of containerization/Docker, Kubernetes - Solid understanding of data warehousing, data lakes, MPP data platforms, and data processing frameworks - Strong understanding of database technologies, including SQL and NoSQL databases. - Experience with CI/CD pipelines and DevOps practices for data engineering - Excellent problem-solving and analytical skills. - Snowflake certification or other relevant data engineering certification is a plus Why you will love being a Dynatracer - Dynatrace is a leader in unified observability and security. - We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance. - Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances. - You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically. - Over 50% of the Fortune 100 companies are current customers of Dynatrace.

Role Description For our client in the telecommunications industry based in Bern, we are looking for an experienced, motivated, and proactive Senior Data Engineer (Kafka). In this project, we are looking for an experienced Senior Data Engineer with a strong focus on Kafka, data architecture, and modern data products. You will play a key role in designing, developing, and integrating scalable data solutions while helping to build and evolve a high-performance data platform. Working in a modern engineering environment, you will contribute to the implementation of event-driven architectures and efficient data processing pipelines. - Analyze and map existing data structures to a centralized data model - Design and define Kafka-based data products - Create event models, data contracts, topic structures, and best practices for Kafka implementations - Develop, implement, and integrate scalable data products using Kafka - Build and optimize event-driven data processing solutions - Ensure an automated data operations lifecycle, including development, deployment, validation, and monitoring - Collaborate closely with architects, developers, and data engineering teams to deliver robust data solutions - Contribute to the continuous improvement of data engineering standards and best practices Qualifications - University degree or equivalent qualification in Computer Science, Data Engineering, or a related field - Several years of experience as a Senior Data Engineer, Data Platform Engineer, or in a similar role - Strong hands-on experience with Apache Kafka, Kubernetes, and Elasticsearch - Expert knowledge of Kafka Streams, ksqlDB, or Apache Flink - Proven experience designing and implementing event-driven architectures and Kafka-based data products - Strong understanding of automated data operations lifecycles (Develop, Deploy, Validate, Observe) - Solid experience with search technologies, especially Elasticsearch - Analytical, structured, and solution-oriented working style - Excellent communication skills and a collaborative mindset - Fluent English (C2 level) Company Description Die Coopers Group AG ist eine agile Schweizer Recruiting Agentur, die Spezialisten und Führungskräfte in den Bereichen IT, Life Sciences, Engineering und Finance vermittelt. Mit flexiblen Ansätzen bringen wir Kandidat:innen und Unternehmen zusammen, die nicht nur fachlich, sondern auch menschlich zusammenpassen.