English language proficiency: minimum B2 level
Technology stack:
SQL
Python
Apache Spark
Apache Beam
Looker
BigQuery
Google Cloud Platform
Vertex AI
Requirements:
Excellent presentation skills
Ability to design and modify data models and select appropriate architectures (DWH, Data Marts, Data Lakes, Delta Lake, Lakehouse, BigLake)
Knowledge of on- premises to GCP migration strategies (lift- and- shift, re- platform, re- architect)
Experience building near real- time data solutions using tools like Pub/Sub and Dataflow
Proficiency with CI/CD and Infrastructure as Code (Terraform and/or Cloud Deploy/Cloud Build), and version control (Git)
Experience in pre- sales engagements, with the ability to translate business requirements into technical solutions
Experience in cloud monitoring, diagnostics, and issue resolution (Cloud Monitoring, Logging, Error Reporting, Cloud Trace), as well as cloud cost planning and optimization (FinOps, GCP Pricing Calculator, BigQuery Reservations)
Familiarity with secure data storage and processing in GCP (VPC Service Controls, CMEK, DLP, Cloud KMS)
Ability to design and scale data pipelines using Dataflow (Apache Beam) and Dataproc, applying best practices for both batch and streaming data processing
Strong analytical skills, self- organization, independence, communication, and proactiveness
Understanding of Lambda and Kappa architectures and their implementation in GCP
Minimum 5 years of experience working with data on Google Cloud Platform (commercial production deployments) and experience as a Lead Developer, Architect, or similar role
Experience optimizing the performance and cost of Dataflow pipelines and Dataproc clusters (e.g., autoscaling, worker sizing), along with implementation of monitoring best practices (Cloud Monitoring, Logging)
Deep understanding of GCP Data & Analytics services (e.g., BigQuery, BigLake, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Dataplex, Sensitive Data Protection, Looker, Vertex AI)
Advanced knowledge of SQL and Python
