Data Engineering Manager – GCP Cloud @ USA Remote Work

Naveera Technology LLC is seeking a Data Engineering Manager to lead an enterprise data platform migration from AWS to GCP. The role combines data architecture and hands-on engineering with migration leadership, team management, and stakeholder collaboration.

Responsibilities:

• Architect and implement scalable enterprise data platforms on GCP
• Design Data Lake and Lakehouse architectures using GCS and BigQuery
• Define Bronze, Silver and Gold/Atomic data layers
• Design scalable data ingestion, transformation and consumption frameworks
• Establish standards for data modeling, partitioning, clustering and storage
• Design multi-tenant and multi-location data architectures
• Define schema-on-read and schema-on-write strategies
• Lead the end-to-end migration of enterprise data platforms from AWS to GCP
• Assess existing AWS architecture, data pipelines, workloads, dependencies and operational processes
• Define the target-state GCP architecture and migration roadmap
• Develop migration strategies for:

Amazon S3 → Google Cloud Storage

Amazon Redshift → BigQuery

AWS Glue → Dataflow / Dataproc / BigQuery

AWS Step Functions → Cloud Composer / Workflows

AWS DMS → GCP-native CDC solutions

Amazon Athena → BigQuery

• Identify opportunities to modernize AWS workloads rather than performing a simple lift-and-shift migration
• Define migration phases, technical dependencies, risks and rollback strategies
• Lead architecture reviews and technical design discussions
• Analyze and optimize existing AWS data platforms before migration
• Work with:

Amazon S3

AWS Glue

AWS Glue Data Quality

Amazon Redshift / Redshift Serverless

Amazon Athena

AWS Step Functions

AWS DMS

AWS Lake Formation

• Understand existing AWS ETL/ELT pipelines, data models, workloads and dependencies
• Identify equivalent or improved GCP services for each AWS workload
• Prepare technical mapping and migration plans between AWS and GCP services
• Architect real-time data pipelines using:

Google Pub/Sub

Dataflow / Apache Beam

BigQuery

Cloud Storage

• Design high-volume event ingestion, enrichment and transformation pipelines
• Implement event-driven architectures and appropriate delivery guarantees
• Optimize streaming pipelines for latency, throughput and scalability
• Design BigQuery streaming ingestion patterns
• Implement monitoring, logging and alerting for real-time workloads
• Design and implement scalable batch and real-time ETL/ELT pipelines
• Migrate AWS Glue-based pipelines to appropriate GCP services
• Develop transformation frameworks using:

Python

PySpark

SQL

Dataflow / Apache Beam

BigQuery

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• Design CDC pipelines and real-time ingestion patterns
• Build orchestration workflows using Cloud Composer / Airflow
• Optimize data processing jobs and query performance
• Design enterprise data models for analytics and reporting
• Define dimensional, normalized and denormalized data models
• Develop multi-tenant data structures
• Design BigQuery partitioning and clustering strategies
• Optimize BigQuery SQL and query execution
• Design data models supporting both real-time and batch workloads
• Work closely with BI and Analytics teams to create scalable consumption models
• Establish data governance and data quality standards across the GCP platform
• Implement automated data quality checks and validation frameworks
• Establish data lineage, metadata and ownership standards
• Ensure appropriate security controls across all GCP data layers
• Implement:

IAM

Least-privilege access

Encryption

Service accounts

Network security

Data access policies

• Work with governance and security teams to ensure compliance requirements are met
• Lead infrastructure automation using Terraform
• Build repeatable and secure GCP infrastructure deployments
• Implement CI/CD pipelines for data engineering workloads
• Work with:

Terraform

Git

GitHub

Cloud Build

CI/CD pipelines

• Automate data pipeline deployment, testing and infrastructure provisioning
• Establish Dev, QA, UAT and Production deployment standards
• Lead performance optimization initiatives across GCP data workloads
• Optimize:

BigQuery query performance

Partitioning and clustering

Dataflow pipelines

Spark workloads

Cloud Storage

Streaming workloads

• Analyze AWS workloads and determine the most cost-effective GCP architecture
• Develop cloud FinOps and cost optimization strategies
• Establish performance benchmarks and SLAs for critical workloads
• Lead and mentor a team of Data Engineers, Senior Data Engineers and Technical Leads
• Provide technical direction and establish engineering standards
• Conduct architecture and code reviews
• Define technical roadmaps and engineering priorities
• Break complex migration requirements into actionable deliverables
• Track engineering progress, risks, dependencies and delivery milestones
• Promote best practices around coding, testing, CI/CD, security and documentation
• Mentor engineers on GCP, data architecture and modern data engineering practices
• Act as the primary technical point of contact for US-based stakeholders
• Work closely with Business, Product, Data Science, BI and DevOps teams
• Translate business requirements into scalable technical solutions
• Present architecture decisions, migration strategies and technical roadmaps
• Communicate technical risks, dependencies, timelines and trade-offs
• Collaborate with business teams to define operational and analytical KPIs

Requirements:

• 15+ Years
• strong hands-on expertise in AWS and GCP Data Engineering
• strong experience designing enterprise data platforms on AWS and migrating them to Google Cloud Platform (GCP)
• strong hands-on experience with AWS services such as S3, Glue, Redshift, Athena, Step Functions and AWS DMS, along with strong GCP expertise across BigQuery, Dataflow, Pub/Sub, Cloud Storage and Cloud Composer
• 15+ years of experience in Data Engineering, Data Architecture or Cloud Engineering
• 5+ years of hands-on GCP Data Engineering experience
• 3+ Yrs Proven experience working on AWS-to-GCP migration projects
• Strong experience designing enterprise Data Lake / Lakehouse platforms
• Experience migrating AWS data workloads to GCP
• Strong knowledge of AWS and GCP service mapping and cloud migration patterns
• Expert-level SQL and strong Python/PySpark skills
• Strong data modeling and data warehousing experience
• Experience with Terraform and CI/CD
• Experience managing and mentoring data engineering teams
• Strong communication skills with experience working with US-based stakeholders
• Amazon S3

AWS Glue

AWS Glue Data Quality

Amazon Redshift / Redshift Serverless

Amazon Athena

AWS Step Functions

AWS DMS

AWS Lake Formation

IAM

• BigQuery

Google Cloud Storage

Pub/Sub

Dataflow / Apache Beam

Cloud Composer / Airflow

Dataproc / Spark

Cloud Monitoring

Cloud Logging

• Advanced Python

Expert-level SQL

Strong PySpark / Apache Spark

ETL/ELT

CDC

Batch and streaming data processing

Event-driven architecture

Data pipeline optimization

• Experience with Dataplex, Data Catalog and data lineage is preferred