Data Pipeline Architect

Vor 7 Tagen

Winterthur, Zürich, Schweiz WinGD – Winterthur Gas & Diesel Vollzeit

Job Summary:

We are seeking an experienced and highly motivated Senior Data Infrastructure Engineer to join our international team at WinGD – Winterthur Gas & Diesel. This team is dedicated to the design and development of the WinGD Integrated Digital Expert (WiDE) product.

Key Responsibilities:

  • Data Infrastructure Management: Ensure the health and economically running of the databases (both cloud-based and edge-based), APIs, and data pipelines.
  • Data Quality and Governance: Ensure data integrity, consistency, and accuracy through the implementation of data validation and quality control measures.
  • Monitoring and Optimization: Monitor and report data systems performance, troubleshoot issues, and optimize processes to enhance data throughput and reliability.
  • Data Pipeline Development: Design, develop, and maintain robust, scalable, and efficient data pipelines for ETL/ELT processes.
  • Automation and Orchestration: Implement automation solutions for data workflows and ensure seamless integration and orchestration of data tasks.
  • Collaboration: Work closely with data analytics teams and operation support experts to understand data requirements and deliver solutions that meet business needs.
  • Security and Compliance: Implement and enforce data security measures and compliance with relevant data protection regulations.
  • Tool and Technology Evaluation: Stay up to date with emerging technologies and tools in the DataOps space and make recommendations for their implementation.

Requirements:

  • Experience: Minimum of 5 years of experience in large-scale data infrastructure management, data engineering, data operations, or a related field, with at least 2 years in a DataOps role. Experienced with time series data and logs handling.
  • Technical Skills: Proficiency in SQL, and experience with databases (e.g., MySQL, DynamoDB, InfluxDB). Familiar with IoT solutions. Familiar with AWS and cloud services (e.g., lambda, S3, Athena). Expertise in Python and script languages. Familiar with data pipeline tools, and big data technologies. Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes). Knowledge of system interfaces, protocols, and standards (e.g., API, Modbus, OPC, MQTT). Experienced in data modeling and database design. Understanding of CI/CD practices and tools (e.g., Jenkins, GitLab CI). Familiar with data security best practices.
  • Soft Skills: Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Ability to work in a fast-paced and agile environment. Detail-oriented with a focus on data quality and accuracy. Clear communication in English both oral and writing.
  • Education: Degree in Computer Science, Information Technology, Engineering, or a related field.

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