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.

• Manage and optimise Snowflake data warehouses. • Overhaul Snowflake warehouse performance through materialisation strategies, dynamic tables, and clustering optimisation. • Build scalable ETL/ELT pipelines using dbt, Airflow, Fivetran, and AWS DMS. • Build ingestion pipelines using DMS and Fivetran. • Develop modelling layers in dbt using medallion architecture principles. • Transform raw data into clean, reliable, and business-ready models using dbt and AI-assisted tooling for documentation and testing. • Integrate data from multiple sources, including CRM systems, payment platforms, gaming platforms, and other operational systems. • Own initiatives focused on data quality improvements and monitoring, including anomaly detection and automated alerting. • Monitor and optimise platform performance, cost efficiency, and security. • Work closely with cross-functional teams across product development, data, operations, and analytics functions. • Collaborate with the data science team and support colleagues with reporting and analytics activities when required. • Support the organisation’s move towards real-time data ingestion and ETL using technologies such as DMS, Kafka, and Kinesis. • Help mentor other engineers within the team. • Contribute to the team's AI strategy and promote effective use of AI tools across engineering workflows. • Produce and maintain clear, comprehensive documentation to support scalability, transparency, and long-term platform sustainability. • Communicate effectively with both technical and non-technical stakeholders and proactively raise blockers when encountered.

• Lead end-to-end data migration activities, including planning, mapping, transformation, validation, and reconciliation. • Define and execute data migration strategies and methodologies for Skadina implementations. • Oversee functional, integration, system, regression, and User Acceptance Testing (UAT) activities. • Ensure data quality, integrity, and consistency throughout migration and deployment phases. • Develop and review test plans, test cases, test scripts, and quality metrics. • Coordinate defect management, issue resolution, and root cause analysis activities. • Collaborate with architects, business analysts, developers, and business stakeholders to ensure successful project delivery. • Support cutover planning, deployment activities, and post-go-live stabilization. • Monitor project quality standards and ensure compliance with established processes and best practices. • Provide technical leadership and mentorship to project teams during migration and testing phases. • Prepare and maintain technical documentation, migration plans, and testing reports.