Data Engineering Manager | GCP to AWS Migration @ Naveera Tech, USA - Remote Work

Greetings of the day!!

I am Arumugam Veera, reaching out to you regarding an exciting career opportunity with Naveera Technology LLC. I would be happy to connect and discuss the opportunity further. You can also connect with me on LinkedIn:https://www.linkedin.com/in/arumugamv/

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, DevOps, API & Systems Integration, Extended Technology Teams & Dedicated Delivery, Real-Time Streaming & Analytics, and BI & Data Warehousing

Job Title: Engineering Manager / Solutions Architect – GCP to AWS Migration Experience: 10+ Years Location: Remote – India Client: USA-Based Client Work Model: Remote supporting US-based stakeholders Domain: Custom Brokerage & Logistics preferred Cloud Focus: GCP → AWS Migration | Data Engineering | Data Architecture

Position Overview

We are looking for an experienced Engineering Manager / Solutions Architect with strong hands-on expertise in GCP and AWS Data Engineering to lead the architecture and execution of a large-scale GCP-to-AWS data platform migration.

The ideal candidate will have a strong background in designing enterprise data platforms, cloud migration strategies, streaming and batch data pipelines, data lakehouse architecture, and modern data governance. The role requires someone who can operate at both architectural and engineering leadership levels, working closely with US-based business and technical stakeholders.

The candidate should have strong experience in GCP data services such as Pub/Sub, Dataflow, BigQuery and Cloud Composer, along with deep AWS expertise across S3, Glue, Redshift, Athena, Step Functions and AWS DMS.

Key Responsibilities

1. Cloud Migration & Architecture

• Lead the end-to-end migration of data platforms from GCP to AWS

• Assess existing GCP architecture, workloads, data pipelines, dependencies and operational processes.

• Define the target-state AWS architecture and migration roadmap.

• Develop migration strategies for BigQuery → Redshift/Snowflake, GCS → S3, Pub/Sub/Dataflow → AWS streaming and Glue-based processing.

• Identify opportunities to modernize existing workloads rather than performing simple lift-and-shift migrations.

• Define architecture standards, design principles, technology selection and reusable patterns.

• Lead technical discussions, architecture reviews and proof-of-concept initiatives.

2. GCP Data Engineering & Streaming

• Architect and implement end-to-end streaming solutions using:

• Google Pub/Sub

Dataflow / Apache Beam BigQuery Cloud Composer / Airflow Google Cloud Storage

• Design real-time ingestion, enrichment and transformation pipelines for high-volume event data.

• Optimize streaming pipelines for latency, throughput, scalability and reliability.

• Design event-driven architectures with appropriate delivery and processing guarantees.

• Define BigQuery schema design, partitioning and clustering strategies.

• Analyze existing GCP workloads and determine the appropriate AWS equivalent during migration.

3. AWS Data Lakehouse Architecture

• Architect enterprise-grade AWS Data Lakehouse solutions using Bronze, Silver and Gold/Atomic layers.

• Design scalable data platforms using:

• Amazon S3

• AWS Glue

• AWS Glue Data Quality

• Amazon Redshift / Redshift Serverless

• Amazon Athena

• AWS Step Functions

• AWS DMS

• Establish data ingestion, transformation, storage and consumption patterns.

• Design multi-tenant data models and scalable schema strategies.

Implement schema-on-read and schema-on-write approaches where appropriate.

• Define Parquet-based storage and partitioning strategies for large-scale datasets.

4. ETL / ELT & Data Processing

• Design and optimize batch and real-time ETL/ELT pipelines.

• Develop scalable transformation frameworks using AWS Glue, PySpark, Python, SQL and dbt.

• Design CDC pipelines using AWS DMS from SQL Server and other OLTP systems.

• Build event-driven workflows using AWS Step Functions and Airflow.

• Optimize Glue workloads, including DPU utilization and execution performance.

• Implement advanced dbt models, testing frameworks and reusable transformation patterns.

• Perform complex SQL optimization and query-performance tuning.

5. Data Modeling & Warehousing

• Define enterprise data models supporting analytics, BI and operational reporting.

• Design dimensional, normalized and denormalized models based on business requirements.

• Develop multi-location and multi-tenant data structures.

• Design Redshift distribution and sort-key strategies.

• Implement partitioning and clustering strategies across cloud data platforms.

• Ensure models support both real-time and batch analytics requirements.

• Work with BI teams to develop scalable semantic and consumption layers.

6. Data Governance, Security & Quality

• Establish enterprise data governance and data quality standards.

• Implement automated data quality gates using AWS Glue Data Quality and dbt tests.

• Establish data lineage, metadata management and data ownership practices.

• Work with governance teams to ensure data integrity and traceability.

• Implement secure data architectures using:

• IAM

• Least-privilege access

• Encryption

• S3 security controls

• Network and access controls

• Experience with AWS Lake Formation is preferred.

• Familiarity with OpenLineage and modern data lineage frameworks is preferred.

• Ensure solutions align with enterprise security and compliance requirements.

7. DevOps, IaC & Automation

• Lead infrastructure automation using Terraform.

• Build repeatable and secure cloud deployment frameworks.

• Implement CI/CD pipelines for data engineering workloads.

• Work with GitHub Actions, Git and cloud-native deployment tools.

• Automate infrastructure, data pipelines, testing and deployment processes.

• Establish environment management across Development, QA, UAT and Production.

• Promote engineering best practices around version control, code reviews and automated testing.

8. Performance & Cost Optimization

• Lead large-scale cloud performance optimization initiatives.

Optimize: AWS Glue DPU consumption Redshift distribution and sort keys S3 storage and Parquet partitioning Athena query performance Data pipeline execution times

• Identify opportunities to reduce AWS infrastructure and processing costs.

Develop FinOps and cloud cost optimization strategies. Establish performance benchmarks and SLAs for critical data workloads.

9. Engieering Management & Technical Leadership

• Provide technical leadership and mentoring to data engineers and architects.

• Lead a team of mid-level and senior data engineering professionals.

• Conduct architecture/design reviews and establish engineering standards.

• Define technical roadmaps aligned with business objectives.

• Break complex requirements into actionable technical deliverables.

• Review technical designs, code and implementation approaches.

• Work with Engineering, DevOps, Data Science, BI and Product teams.

• Help build engineering capabilities, reusable frameworks and best practices.

10. Stakeholder & Client Management

• Act as the primary technical liaison with US-based stakeholders.

• Work directly with business leaders, product teams, Data Science and BI teams.

• Translate business and operational requirements into scalable technical solutions.

• Present architecture decisions, migration strategies and technical roadmaps to senior stakeholders.

• Communicate risks, dependencies, timelines and technical trade-offs effectively.

• Support business teams in defining enterprise and clinical/operational KPIs.

Tasks

• Required Experience & Qualifications

• 10+ years of experience in Data Engineering, Data Architecture or Cloud Engineering.

• 3+ years of hands-on GCP Data Engineering experience.

• Strong hands-on experience with AWS Data Engineering and Architecture.

• Proven experience leading or contributing to GCP-to-AWS migration projects.

• Experience designing large-scale data lake/lakehouse platforms.

• Strong experience with streaming and event-driven architectures.

• Expert-level SQL, Python and PySpark skills.

• Strong data modeling and data warehousing experience.

• Experience with Terraform and CI/CD.

• Proven ability to lead technical teams and mentor engineers.

• Strong communication skills with the ability to interact directly with US-based stakeholders.

• Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering or a related technical field.

• AWS Certified Solutions Architect – Professional.

• AWS Certified Data Engineer – Associate.

• Google Cloud Professional Data Engineer certification.

• Experience with Healthcare or Insurance domain.

• Understanding of HIPAA and healthcare data security requirements is a plus.

• Experience with Microsoft Fabric and Power BI integration.

• Experience with Power BI Embedded and cloud-hosted applications.

• Experience defining healthcare/clinical KPIs, operational metrics, referral metrics or conversion metrics.

• Leadership & Core Competencies

• Cloud Migration Leadership: Proven ability to lead complex GCP-to-AWS migration initiatives.

• Solution Architecture: Ability to translate business requirements into scalable enterprise architectures.

• Engineering Leadership: Strong team management, mentoring and technical decision-making skills.

• Data Architecture: Expertise in Lakehouse, Data Warehouse, Streaming and Data Modeling.

• Performance Engineering: Strong understanding of scalability, latency and cloud optimization.

• FinOps: Ability to identify and implement cloud cost optimization opportunities.

• Data Governance: Strong understanding of security, quality, lineage and compliance.

• Stakeholder Management: Excellent communication and ability to work with US-based technical and business stakeholders.

Requirements

• Required Technical Skills

• Cloud & Migration

• GCP: Pub/Sub, Dataflow, BigQuery, Cloud Composer, GCS

• AWS: S3, Glue, Glue Data Quality, Redshift, Athena, Step Functions, AWS DMS

• Strong understanding of GCP-to-AWS cloud migration

• Experience designing target-state cloud architectures.

• Data Engineering

• Advanced Python

• Expert-level SQL

• Strong PySpark / Apache Spark

• Advanced ETL/ELT concepts

• CDC and event-driven architecture

• Real-time and batch processing

• Data Architecture

• Data Lake / Lakehouse Architecture

• Medallion Architecture – Bronze, Silver and Gold

• Data Modeling

• Dimensional Modeling

• Multi-tenant Data Modeling

• Schema-on-Read / Schema-on-Write

• Data Lineage and Metadata Management

• AWS

• AWS Glue

• AWS Glue Data Quality

• Amazon Redshift / Redshift Serverless

• Amazon S3

• Amazon Athena

• AWS Step Functions

• AWS DMS

• AWS Lake Formation

• IAM and security best practices

• GCP

• Google Pub/Sub

• Dataflow / Apache Beam

• BigQuery

• Cloud Composer / Airflow

• Google Cloud Storage

• Cloud Monitoring / Logging

• Modern Data Stack

• dbt

• Apache Airflow

• Terraform

• Git / GitHub

• CI/CD

• OpenLineage

• Data Quality Frameworks

Benefits

• Lead large-scale AWS-to-GCP cloud transformation initiatives.

• Work on enterprise Data Lakehouse and analytics modernization projects.

• Opportunity to migrate enterprise BI platforms from Qlik Sense to Looker.

• Flexible remote work environment.

• Exposure to global enterprise customers.

• Collaborative, innovation-driven engineering culture.

• Continuous learning and certification opportunities.

Join Naveera Technology LLC and play a pivotal role in delivering enterprise-scale AWS-to-GCP cloud transformation programs. Lead the modernization of data platforms, ETL pipelines, and analytics ecosystems while driving innovation across cloud-native data engineering, Data Lakehouse architectures, and next-generation Business Intelligence solutions.