Google Cloud Platform Data Engineer Consultant

GCP Data Engineer - Consultant

 

Job Requirements:-

• Bachelors or higher degree in Computer Science or a related discipline; or equivalent (minimum 4+ years work experience).

 • At least 4+ years of consulting or client service delivery experience on Google Cloud Platform (GCP). 

• At least 4+ years of experience in developing data ingestion, data processing, and analytical pipelines for big data, relational databases such as Cloud SQL, and data warehouse solutions such as BigQuery. 

• Extensive experience providing practical direction with using GCP Native services. 

• Extensive hands-on experience implementing data ingestion, ETL, and data processing using GCP services: Google Cloud Storage (GCS), Dataflow, Cloud Functions, Cloud Composer, BigQuery, Cloud SQL, Pub/Sub, IoT Core, Dataproc, Dataprep, Bigtable, Firestore, etc. 

• Minimum of 4+ years of hands-on experience in GCP and Big Data technologies such as Java, Python, SQL, GCS, Apache Beam, PySpark, and SparkSQL, Dataproc, and live streaming technologies such as Pub/Sub, Dataflow, etc. 

• Well versed in DevSecOps and CI/CD deployments. 

• Cloud migration methodologies and processes including tools like Cloud Dataflow and Database Migration Service. 

• Minimum of 4+ years of RDBMS experience. 

• Experience in using Big Data File Formats and compression techniques. 

• Experience working with Developer tools such as Cloud Build, IntelliJ IDEA, Git, Jenkins, etc. 

• Experience with private and public cloud architectures, pros/cons, and migration considerations.

Primary Roles and Responsibilities:-

A Google Cloud Data Engineer is responsible for designing, building, and maintaining the data infrastructure for an organization using Google Cloud Platform (GCP) services. This includes creating data pipelines, integrating data from various sources, and implementing data security and privacy measures. The Google Cloud Data Engineer will also be responsible for monitoring and troubleshooting data flows and optimizing data storage and processing for performance and cost efficiency.

  Preferred Skills:-

       • DevOps on a Google Cloud Platform (GCP). 

     • Experience developing and deploying ETL solutions on Google Cloud. 

     • Familiarity with Google Cloud Data Catalog for metadata management, Data Governance, Data     Lineage, Data Catalog, etc.

    • Knowledge of Google Cloud IAM (Identity and Access Management). Understanding access controls     and security on Google Cloud. 

• Inclined with Google's vision and roadmap around the latest tools and technologies in the market. 

• Knowledge on Google Cloud's Vertex AI, Machine Learning capabilities, and industry supporting use cases. 

• Google Cloud certifications role-based (e.g., Professional Data Engineer, Professional Cloud Architect, Associate Cloud Engineer, Professional Machine Learning Engineer, etc.) 

• Google Looker Studio (formerly Google Data Studio) hands-on and working knowledge, to create reports/dashboards and generate insights for business users.

 

 

 

Experience Level

Mid Level