SeniorPrinciple GCP Data Engineer with strong SQL and Python
SeniorPrinciple GCP Data Engineer with strong SQL and Python
Posted on :
23-09-2024
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Job Description
Contact Details:
1.Savitha Chinnappa
Email:
Cell: (732)
Email:
Cell: (732)
2.Pio Dhivagar
Email:
Cell: (732)/ Ext.420
Email:
Cell: (732)/ Ext.420
Location: Remote
Duration: 6 Months CTH
Years of Experience: 10 Yrs.
Required Hours/Week: 40hrs./Week
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 Required:
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.
Employment Type
Full Time
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