Data Engineer

Vor 6 Tagen

Zürich, Zürich, Schweiz Loryven Vollzeit

Role Description

The Data Engineer is responsible for designing, developing, and maintaining data infrastructure and pipelines that enable efficient data collection, storage, and analysis across the organization. This role focuses on building scalable systems that transform raw data into reliable and structured formats for business intelligence, analytics, and machine learning applications. The ideal candidate possesses strong technical expertise, problem-solving skills, and a deep understanding of data architecture and cloud-based technologies.

Key Responsibilities

  • Design, build, and maintain scalable data pipelines and ETL processes to collect, transform, and integrate data from multiple sources.
  • Develop and optimize data models, databases, and warehouse structures for analytics and reporting.
  • Collaborate with data scientists, analysts, and business teams to define data requirements and deliver high-quality datasets.
  • Implement data validation, cleansing, and transformation workflows to ensure data accuracy and reliability.
  • Manage and monitor data infrastructure on cloud platforms such as AWS, Azure, or Google Cloud.
  • Develop APIs and data integration frameworks to enable seamless data flow across systems.
  • Optimize query performance and data storage to improve system efficiency and scalability.
  • Establish and maintain data governance, security, and privacy standards in compliance with organizational policies.
  • Automate data workflows, monitoring, and alerting to reduce manual intervention.
  • Document data architecture, processes, and pipelines for maintainability and knowledge sharing.
  • Troubleshoot and resolve data-related issues and ensure minimal downtime in data services.
  • Evaluate and recommend emerging technologies and tools to enhance data infrastructure capabilities.
  • Support data migration, system upgrades, and integration projects across departments.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
  • 2–5 years of experience in data engineering, data architecture, or related roles.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Strong knowledge of SQL and experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB).
  • Hands-on experience with ETL tools and frameworks such as Apache Airflow, Spark, or Kafka.
  • Familiarity with cloud data platforms like AWS Redshift, Google BigQuery, or Azure Data Lake.
  • Understanding of data modeling, data warehousing, and distributed computing principles.
  • Experience with version control systems (Git) and CI/CD pipelines.
  • Strong problem-solving, analytical, and communication skills.
  • Knowledge of data governance, security, and compliance best practices.
  • Ability to work collaboratively in cross-functional teams and adapt to evolving technologies.
  • Certifications in cloud or data engineering (e.g., AWS Data Engineer, Google Cloud Professional Data Engineer) are advantageous.

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