Data Engineer

vor 8 Stunden

Berlin, Berlin, Deutschland Orvexay Vollzeit 90.000 € - 120.000 € pro Jahr

Role Description

The Data Engineer is responsible for designing, building, and maintaining robust and scalable data infrastructure to support analytics, business intelligence, and machine learning initiatives. This role involves creating efficient data pipelines, transforming raw data into structured formats, and ensuring data quality, reliability, and accessibility across the organization. The Data Engineer collaborates with data scientists, analysts, and software engineers to provide actionable insights and drive data-driven decision-making. The ideal candidate has strong technical expertise, problem-solving abilities, and a passion for working with large and complex datasets.

Key Responsibilities

  • Design, develop, and maintain ETL/ELT pipelines to extract, transform, and load data from multiple sources.
  • Build and manage data warehouses, data lakes, and data marts to support reporting and analytics requirements.
  • Optimize data storage, processing, and retrieval for performance, scalability, and cost efficiency.
  • Collaborate with data scientists, analysts, and business teams to understand data requirements and provide accessible datasets.
  • Implement data quality checks, validation, and monitoring processes to ensure accuracy and consistency.
  • Integrate data from APIs, databases, cloud platforms, and external systems into unified repositories.
  • Automate data workflows and maintain reusable frameworks for data processing.
  • Monitor and maintain data infrastructure, troubleshoot issues, and implement performance improvements.
  • Ensure compliance with data governance, privacy, and security standards.
  • Contribute to technical documentation, including data models, pipeline workflows, and architecture diagrams.
  • Stay up-to-date with emerging data technologies, tools, and best practices to enhance infrastructure and workflows.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
  • 2–5 years of experience in data engineering, ETL development, or database management.
  • Proficiency in SQL and programming languages such as Python, Scala, or Java.
  • Experience with data pipeline orchestration tools (Airflow, Prefect, Luigi, etc.).
  • Familiarity with cloud-based data platforms such as AWS (Redshift, Glue, S3), Azure (Data Factory, Synapse), or Google Cloud (BigQuery, Dataflow).
  • Experience with relational and non-relational databases (PostgreSQL, MySQL, MongoDB, Cassandra, etc.).
  • Understanding of data modeling, schema design, and data warehousing principles.
  • Knowledge of distributed data processing frameworks (Spark, Hadoop, Kafka) is an advantage.
  • Strong analytical, problem-solving, and troubleshooting skills.
  • Excellent communication and teamwork abilities for cross-functional collaboration.
  • Familiarity with CI/CD pipelines, DevOps practices, and infrastructure-as-code (IaC) is a plus.
  • Passion for data-driven innovation, continuous learning, and emerging technologies.

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