Senior/Principle GCP Data Engineer with strong SQL and Python

Role: Senior/Principle GCP Data Engineer with strong SQL and Python Location- RemoteDuration- 6 Months C2HOpenings - 6 PositionsSteer ClearNo one < 3 years of experience on GCPNo one with only experience in AWS and AzureData Engineering RequirementProgrammingSQLPythonJava (Optional)GCPBigQueryDataflow (Apache Beam)Cloud Composer (Airflow)GCSGKEDataform (Optional to dbt)Toolsdbt / Dataform(On GCP)Test Automation on DataMisc.(Good To Have)DockerKubernetesMicroservicesExperienceData Platform Building (Mandatory)Ingestion/MigrationTransformation/ETLAnalysis (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 ACL's, Row/Column level in BigQuery)DeploymentCI/CDGithubCloud Build (Service in GCP) + TerraformRequirements10-15+ (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 end-to-end 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 MustExperience with Microservices architectures - Kubernetes, Docker and Cloud RunExperience 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.Hands-on 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.