You will design and build data engineering solutions using Google Cloud Platform (GCP) services.
Responsibilities
Design and develop data modules that convert raw data into usable formats for reporting.
Extract, load, transform, clean, and validate data using cloud ETL/ELT tools.
Monitor and improve the quality of components throughout the development lifecycle.
Identify application bottlenecks and opportunities to optimize performance.
Troubleshoot production issues and coordinate code deployment with the support team.
Required Skills
4+ years of hands-on experience with GCP Suite, including Tera Data, BigQuery, PubSub, Data Fusion, Google Cloud Storage, DataProc, Composer, and Looker.
Solid understanding of Google Cloud architecture and GCP Compute, Storage, Data, Network, and Security.
5+ years of working experience with tools such as Spark, HBase, Sqoop, Impala, Kafka, Flume, Oozie, and MapReduce.
Strong experience in SQL and Data warehousing.
Experience with Cloud Data Flow, Cloud Pub Sub, Cloud BigTable, ML APIs, and AutoML.
Familiarity with Cloud ML Serverless Architecture and Security, including Cloud Functions and Cloud IAM.
Proficiency in GCP services, including Bigquery.
Experience with DevOps and Big Data practices on Google Cloud.