Gana IT

Location: Remote / Tampa, FL

Experience: 0 Years

Skills: GCP, Python, Terraform, Docker, Jenkins, GitLab CI/CD, Kubernetes, JavaScript, REST APIs

Description:

Develop and deploy cloud-native applications on Google Cloud Platform (GCP).
Implement CI/CD pipelines using GitLab CI/CD and Jenkins for automated deployments.
Manage infrastructure as code using Terraform and Cloud Deployment Manager.
Build Docker images and manage container orchestration with Kubernetes (GKE).
Automate service deployments and configurations using shell scripts and Python.
Monitor cloud resources and set up logging/alerting using Stackdriver (Cloud Monitoring).
Integrate IAM roles, service accounts, and workload identity for secure access.
Write scalable backend APIs in Python and Node.js.
Use Firestore and Cloud SQL for managing application data.
Implement version control using Git, branching strategies, and merge pipelines.
Participate in code reviews and agile sprints for feature enhancements.
Write unit, integration, and automated tests to improve code quality.
Build responsive front-ends with HTML, CSS, Bootstrap, and JavaScript frameworks.
Collaborate with product managers and QA teams to release stable features.
Participate in performance tuning, cost optimization, and GCP billing analysis.

Location: Hybrid – Tampa, FL

Experience: 4+ Years

Skills: BigQuery, Dataflow, Python, Airflow, ETL, GCS, Pub/Sub, SQL, Spark

Description:

Design, build, and manage data pipelines on Google Cloud using Dataflow and BigQuery.
Ingest structured and unstructured data from APIs, databases, and flat files.
Orchestrate workflows using Apache Airflow and Cloud Composer.
Write scalable data processing scripts in Python and PySpark.
Automate ETL/ELT processes and ensure data integrity and validation.
Use Pub/Sub for real-time streaming and event-based architecture.
Load and transform data in BigQuery using SQL, UDFs, and partitioning.
Optimize performance and cost for cloud storage and processing jobs.
Work with Data Studio and Looker for data visualization and dashboarding.
Implement GCS lifecycle policies for archival and retention of raw data.
Perform data quality checks and anomaly detection across multiple datasets.
Collaborate with analytics, product, and engineering teams to define data needs.
Document data dictionaries, pipeline configurations, and lineage.
Maintain secure access with IAM, VPC Service Controls, and DLP policies.
Conduct peer code reviews and implement continuous improvements in pipeline efficiency.

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