SeniorPrinciple GCP Data Engineer with strong SQL and Python

Role: Senior/Principle GCP Data Engineer with strong SQL and Python
Location Remote
Duration 6 Months C2H
Openings 6 Positions

Steer Clear
No one < 3 years of experience on GCP
No one with only experience in AWS and Azure

Data Engineering Requirement

Programming
SQL
Python
Java (Optional)

GCP
BigQuery
Dataflow (Apache Beam)
Cloud Composer (Airflow)
GCS
GKE
Dataform (Optional to dbt)

Tools
dbt / Dataform(On GCP)
Test Automation on Data

Misc.(Good to Have):
Docker
Kubernetes
Microservices

Experience:

Data Platform Building (Mandatory)

Ingestion/Migration
Transformation/ETL
Analysis (Optional)
Visualization
(SAP BOBJ/Looker/PowerBI)
Governance
(Unitiy Catalog(tool in databricks)/Colibra(tool)/Data Catalog(Service in GCP)
Security
(GCP Services IAM KMS DLP. Techniques ACLs Row/Column level in BigQuery)

Deployment

CI/CD
Github
Cloud Build (Service in GCP) Terraform

Requirements:

• 1015 (for senior) of proven experience in modern cloud data engineering broader data landscape experience and exposure and solid software engineering experience.
• Prior experience architecting and building successful enterprise scale data platforms in a green field environment is a must.
• Proficiency in building endtoend data platforms and data services in GCP is a must.
• Proficiency in tools and technologies: BigQuery Cloud Functions Cloud Run Dataform Dataflow Dataproc SQL Python Airflow PubSub. SQL/Python Must
• Experience with Microservices architectures Kubernetes Docker and Cloud Run
• Experience building Symantec layers.
• Proficiency in architecting and designing and development experience with batch and real time streaming infrastructure and workloads.
• Solid experience with architecting and implementing metadata management including data catalogues data lineage data quality and data observability for big data workflows.
• Handson experience with GCP ecosystem and data lakehouse architectures.
• Strong understanding of data modeling data architecture and data governance principles.
• Excellent experience with DataOps principles and test automation.
• Excellent experience with observability tooling: Grafana Datadog.