The position involves an expert who will concentrate on the planning, deployment, and optimization of our network and data architecture on the Google Cloud Platform (GCP) and has fundamental experience in Microsoft Azure. The ideal applicant will excel in comprehensive data engineering and demonstrate strong network management capabilities within cloud platforms.

#LI-DNI

Responsibilities

Develop and manage secure, well-regulated cloud infrastructures primarily on GCP and Azure
Build and sustain scalable and reliable cloud network structures utilizing GCP Networking
Create and implement data pipelines using PySpark, ensuring data quality and governance
Employ Google Cloud Dataflow and Google Cloud Pub/Sub for data processing and event-based architectures
Apply infrastructure as code using Terraform for consistent and reproducible infrastructure setup
Oversee continuous integration and continuous deployment (CI/CD) strategies for data pipelines
Analyze and enhance the performance of SQL and Python applications
Work collaboratively with the team to develop our Kubernetes environment, focusing on scalability and security
Progress the organization's proficiency in data modeling and augment existing data architectures
Adhere to security best practices and organizational policies

Requirements

Minimum of 5 years in network and data engineering
At least 1 year of relevant leadership experience
Profound knowledge and experience with GCP cloud computing, networking, and infrastructure
Basic skills in Azure Networking and Azure Identity/Principal Management
Proficiency in Python, PySpark, and SQL
Prior use of Databricks and extensive expertise in Kubernetes
Familiarity with Cloud Dataflow, Cloud Pub/Sub, and Cloud Storage
Capability to engineer and sustain data pipelines on PySpark
Management of data quality and governance requirements
Expertise in Infrastructure as Code using Terraform
Background in CI/CD processes for data pipelines