Associate Data Practitioner

As an Associate Data Practitioner, I am equipped to secure and manage data effectively on Google Cloud. My experience encompasses a wide range of Google Cloud data services, enabling me to proficiently handle tasks such as data ingestion, transformation, pipeline management, analysis, machine learning, and visualization. I also possess a foundational understanding of core cloud computing concepts including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS).

My capabilities include preparing and ingesting data by differentiating between various data manipulation methodologies like ETL, ELT, and ETLT, and selecting appropriate data transfer tools such as Storage Transfer Service or Transfer Appliance. I can assess data quality and perform data cleaning using tools like Cloud Data Fusion, BigQuery, SQL, and Dataflow. I am skilled in extracting data in multiple formats, including CSV, JSON, Apache Parquet, and Apache Avro, and loading it into suitable Google Cloud storage systems such as Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, or Spanner, using tools like Dataflow, BigQuery Data Transfer Service, and Database Migration Service. For analysis and presentation, I can identify data trends using BigQuery and Jupyter notebooks like Colab Enterprise, execute SQL queries, and create insightful dashboards in Looker. Furthermore, I can define, train, evaluate, and utilize machine learning models through BigQuery ML and AutoML, including leveraging pretrained Google large language models (LLMs) and managing models in the Model Registry.

I am proficient in designing and implementing simple data pipelines, selecting the right transformation tools such as Dataproc, Dataflow, Cloud Data Fusion, Cloud Composer, or Dataform based on specific business requirements, and evaluating use cases for ELT and ETL. I can schedule, automate, and monitor data processing tasks using services like Cloud Scheduler and Cloud Composer, review logs in Cloud Logging and Cloud Monitoring, and implement event-driven architectures with Pub/Sub and Eventarc. In terms of data management, I can configure robust access control and governance following the principle of least privilege with Identity and Access Management (IAM), manage data lifecycles effectively across services like Cloud Storage and BigQuery, and identify high availability and disaster recovery strategies. My expertise also covers applying crucial security measures, including managing encryption keys with Cloud Key Management Service (Cloud KMS) and understanding different encryption methods like CMEK, CSEK, and GMEK, to ensure data privacy and compliance.