Описание
Accountabilities
- Design, develop, and maintain scalable data pipelines to support large-scale data processing and analytics requirements.
- Architect and implement robust data solutions using modern data engineering principles, distributed processing technologies, and cloud platforms.
- Design and optimize advanced SQL queries to improve performance and efficiency in analytical environments.
- Manage and optimize relational and non-relational databases, applying performance tuning and scalability strategies.
- Build and maintain data processing workflows using Apache Spark with Scala or PySpark, alongside Python or Java programming.
- Implement and optimize data architectures based on Data Lake and Lakehouse concepts to support evolving business and technical needs.
- Work with distributed data processing frameworks such as Databricks and Apache Flink, as well as orchestration tools such as Apache Airflow or Google Cloud Composer.
- Support the implementation and maintenance of streaming data solutions to enable efficient data processing and integration.
- Leverage cloud services and infrastructure on Google Cloud Platform (GCP) or Amazon Web Services (AWS) to build reliable and scalable data platforms.
- Collaborate with technical teams and business stakeholders to understand requirements, define architectural approaches, and deliver effective data solutions.
- Contribute to digital transformation initiatives by developing data engineering capabilities that support innovat
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