Google Recruitment 2023

As a Data Engineer at Google, you will be responsible for designing, developing, and maintaining data pipelines and infrastructure to ensure efficient and reliable data processing and storage. You will collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and implement robust data solutions. With your expertise in data engineering, programming, and cloud technologies, you will contribute to building scalable and performant data systems that enable data-driven insights and applications.

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Responsibilities:

1. Data Pipeline Development: Design and develop scalable data pipelines to ingest, transform, and load large volumes of data from various sources. Implement data integration and ETL (Extract, Transform, Load) processes using industry best practices and frameworks. Ensure data quality, reliability, and integrity throughout the pipeline.
2. Data Modeling and Warehousing: Design and implement data models and schemas for efficient data storage and retrieval. Develop and maintain data warehouses and data marts that support business analytics and reporting needs. Optimize data structures and queries for performance and scalability.
3. Data Transformation and Processing: Implement data transformation logic and algorithms to convert raw data into meaningful insights. Perform data cleansing, normalization, and aggregation to enable advanced analytics and machine learning. Collaborate with data scientists to operationalize and deploy machine learning models.

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Skills and Qualifications:

• Familiarity with cloud platforms, such as Google Cloud Platform (GCP), AWS, or Azure.
• Knowledge of data integration tools and ETL frameworks, such as Apache Beam or Airflow.
• Strong problem-solving and analytical skills with the ability to troubleshoot and optimize data processes.