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Data Engineering Manager – GCP Cloud Remote Work

Remote / Online - Candidates ideally in
Hempstead, Nassau County, New York, 11549, USA
Listing for: Naveera Technology LLC
Full Time, Remote/Work from Home position
Listed on 2026-10-29
Job specializations:
  • IT/Tech
    Cloud Computing: Infrastructure & Operations, Data Engineering, AWS
Salary/Wage Range or Industry Benchmark: 180000 - 240000 USD Yearly USD 180000.00 240000.00 YEAR
Job Description & How to Apply Below
About Naveera Technology LLC

Naveera Technology LLC is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development, and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting, we help organizations transform raw data into actionable business value.

With a team of 100+ employees and successful delivery of 3+ global projects, Naveera serves clients across multiple industries and geographies through agile delivery models and proven engineering practices.

From Digital Health and Financial Services to E-Commerce and Technology, we support a diverse client base and back every engagement with proven frameworks, low-attrition teams, and scalable global delivery capabilities. At Naveera, we empower organizations to turn challenges into opportunities, data into insights, and innovative ideas into enterprise-grade platforms.

Specialties

Data Engineering & Modern Data Stack, Generative AI Solutions & Model Deployment, Application Development (Web, Mobile & Enterprise), Artificial Intelligence (Predictive, Conversational, Computer Vision), IT Infrastructure Services (Cloud & On-Prem), Security, DR, Cloud Transformation & Microservices, Dev Ops, API & Systems Integration, Extended Technology Teams & Dedicated Delivery, Real-Time Streaming & Analytics, and BI & Data Warehousing

Job Title:

Data Engineering Manager – GCP Cloud

Experience:

15+ Years

Location:

Remote (USA)
Primary Focus: GCP Data Engineering |AWS → GCP Migration | Data Engineering | Data Architecture | Engineering Leadership

Position Overview

We are looking for an experienced Engineering Manager with strong hands‑on expertise in AWS and GCP Data Engineering to lead a large-scale AWS-to-GCP data platform migration.

The ideal candidate will have strong experience designing enterprise data platforms on AWS and migrating them to Google Cloud Platform (GCP). The role requires a combination of technical architecture, hands‑on engineering, migration leadership, team management and stakeholder management.

The candidate should have strong hands‑on experience with AWS services such as S3, Glue, Redshift, Athena, Step Functions and AWS DMS, along with strong GCP expertise across Big Query, Dataflow, Pub/Sub, Cloud Storage and Cloud Composer.

The Engineering Manager will work closely with US‑based stakeholders, architects, engineers, Dev Ops teams, Data Science and BI teams to define the migration strategy and ensure successful execution.

Key Responsibilities
1. GCP Data Platform Architecture

Architect and implement scalable enterprise data platforms on GCP.

Design Data Lake and Lakehouse architectures using GCS and Big Query.

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.

2. AWS to GCP Migration Leadership

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 → Big Query

AWS Glue → Dataflow / Dataproc / Big Query

AWS Step Functions → Cloud Composer / Workflows

AWS DMS → GCP‑native CDC solutions

Amazon Athena → Big Query

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.

3. AWS…
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