Data Migration Architect – AWS, GCP

🔥 0 minutes ago

🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

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Naveera Technology LLC

WebsiteLinkedInAll Job Openings

201 - 500 employees

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

Artificial Intelligence • B2B • Enterprise

Naveera Technology LLC is a technology consulting and engineering firm that helps businesses become AI-first by building production-ready data engineering, machine learning, generative AI, application development, and IT infrastructure solutions. The company delivers end-to-end services—from data pipelines and cloud infrastructure to GenAI model development, MLOps, and custom web/mobile enterprise applications—focused on turning raw data into actionable intelligence and scalable systems. Naveera serves industries such as digital health, fintech, e-commerce, and enterprise clients through global delivery, extended teams, and a center-of-excellence model.

📋 Description

• Lead end-to-end migration of enterprise data platforms from AWS to Google Cloud Platform • Design migration strategies for AWS Redshift, Glue, S3, DynamoDB, Data Lakes, Data Warehouses, and ETL pipelines into GCP-native services • Modernize existing AWS data architectures using Google Cloud best practices • Assess existing AWS environments and recommend optimized GCP solutions • Ensure seamless migration with minimal business disruption • Design scalable batch and streaming data pipelines using Google Dataflow (Apache Beam) • Develop event-driven architectures using Google Pub/Sub • Build enterprise analytical solutions using BigQuery, including streaming inserts and performance optimization • Develop and orchestrate workflows using Cloud Composer (Apache Airflow) • Manage enterprise-scale storage using Google Cloud Storage (GCS) • Implement cloud-native data engineering solutions following Google Cloud best practices • Design, develop, and optimize ETL/ELT pipelines using AWS Glue and AWS Glue DataBrew • Work extensively with Amazon Redshift, Amazon S3, and DynamoDB • Develop scalable ETL workflows using Python, PySpark, and SQL • Build and maintain Data Lakehouse architectures supporting enterprise analytics • Optimize data ingestion, transformation, and loading processes across hybrid cloud environments • Design modern Data Lakehouse, Data Warehouse, and Data Lake architectures • Develop dimensional data models, star schemas, and optimized analytical datasets • Build transformation pipelines using DBT (Data Build Tool) • Write and optimize complex SQL queries for high-performance analytics • Ensure data quality, governance, metadata management, and performance optimization • Lead migration of enterprise dashboards from Qlik Sense to Looker • Translate business reporting requirements into scalable semantic models • Optimize reporting performance using BigQuery and LookML best practices • Collaborate with business stakeholders to modernize enterprise reporting platforms • Lead architecture design sessions and cloud migration workshops • Mentor Data Engineers and establish engineering best practices • Conduct architecture, code, and design reviews • Collaborate with business, DevOps, QA, and Analytics teams • Coordinate effectively with onsite and offshore delivery teams • Implement enterprise security standards across AWS and GCP • Define IAM, encryption, auditing, and monitoring strategies • Ensure compliance with governance and regulatory standards • Establish data quality frameworks and operational monitoring • Gather business requirements and define cloud migration roadmaps • Estimate project efforts and prepare technical solution documents • Manage project timelines, risks, dependencies, and stakeholder communications • Present technical architecture and migration strategies to leadership and clients

🎯 Requirements

• 10+ years of overall experience • Hands-on AWS & GCP Data Engineering expertise • AWS to GCP Migration • Google Cloud Platform (GCP) • Google Pub/Sub • Dataflow (Apache Beam) • BigQuery • Cloud Composer (Airflow) • Google Cloud Storage (GCS) • AWS Redshift • AWS Glue • AWS Glue DataBrew • Amazon S3 • DynamoDB • DBT (Data Build Tool) • SQL • Python • PySpark • Data Lakehouse • ETL/ELT • Qlik Sense to Looker Migration • Cloud SQL • Terraform • CI/CD

🏖️ Benefits

• Flexible remote work environment • Exposure to global enterprise customers • Collaborative, innovation-driven engineering culture • Continuous learning and certification opportunities