Job Title: Google Cloud Platform Data Architect / Senior Data Engineer Location: Dallas - TX Locals are first priority
Position Overview:
We are seeking a Google Cloud Platform Data Architect / Senior Data Engineer with advanced expertise in Google Cloud Platform (Google Cloud Platform) to lead the design, architecture, and optimization of cloud-based data systems. In this role, you will drive data migration, architect ETL processes, and build scalable data solutions to support high-impact business intelligence and analytics.
Key Responsibilities:
Google Cloud Platform Architecture:
o Architect and optimize data solutions using BigQuery, with a focus on data partitioning, clustering, and cost-effective querying.
o Manage and configure Cloud Dataflow for ETL workflows and data processing, and orchestrate data pipelines using Cloud Composer (Apache Airflow).
o Leverage additional Google Cloud Platform tools like Cloud Storage, Pub/Sub, and IAM to enhance data security, integration, and scalability.
ETL & Data Pipeline Development:
o Design and implement ETL pipelines with tools like Apache Airflow, Talend, Informatica, or custom frameworks, ensuring robust data flow across systems.
o Use Python and SQL for automation and data processing, ensuring high-performance, cost-efficient workflows.
Data Warehousing Architecture:
o Develop and maintain data warehouse architectures that support complex data models (e.g., star schema, snowflake schema).
o Ensure data governance, compliance, and quality standards, particularly around data structures and data modeling in BigQuery.
o Optimize query performance, leveraging advanced SQL skills to manage and analyze data effectively.
Data Migration and Integration:
o Lead data migration from on-premise warehouses (e.g., Teradata, Netezza) to Google Cloud Platform, ensuring data accuracy and security.
o Utilize data transfer tools (e.g., gsutil, BigQuery Data Transfer Service) and develop custom solutions for efficient, secure data migration.
o Design and integrate data pipelines across diverse sources using APIs, webhooks, and other integration methods, supporting seamless data connectivity.
Qualifications:
Technical Expertise: Proven experience with Google Cloud Platform services, especially BigQuery, Cloud Dataflow, and Cloud Composer.
ETL & Automation: Advanced skills in Python, SQL, and ETL tools for data processing and automation.
Data Architecture: Strong understanding of data warehouse design, data modeling, and cloud data optimization.
Migration Experience: Demonstrated success in migrating on-premise data warehouses to cloud environments.
Data Governance: Knowledge of data governance principles and compliance frameworks for secure, compliant data handling.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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