Data Engineering Manager – GCP Cloud @ USA Remote Work

Naveera Technology LLC

3d • $120,000 - $160,000 • Remote

About The Position

Naveera Technology LLC is seeking an experienced Engineering Manager to lead a large-scale migration of enterprise data platforms from AWS to Google Cloud Platform (GCP). The role combines technical architecture, hands-on data engineering, migration leadership, team management, and stakeholder engagement. The manager will work with US-based stakeholders, architects, engineers, DevOps, Data Science, and BI teams to define and execute the migration strategy.

The position involves designing scalable GCP data platforms, including data lake and lakehouse architectures, layered data models, ingestion and transformation frameworks, streaming pipelines, and analytics models. It also entails assessing existing AWS workloads and dependencies; defining target-state GCP architecture, migration phases, risks, and rollback strategies; and identifying modernization opportunities beyond lift-and-shift migration.

The manager will lead data governance, quality, security, infrastructure automation, CI/CD, performance, and cost optimization efforts. They will provide technical direction, establish engineering standards, mentor data engineers and technical leads, track delivery milestones, and communicate architecture decisions, risks, timelines, and trade-offs to stakeholders.

Requirements

• 15+ years of experience in Data Engineering, Data Architecture, or Cloud Engineering.
• 5+ years of hands-on GCP Data Engineering experience.
• 3+ years of proven experience working on AWS-to-GCP migration projects.
• Strong experience designing enterprise data lake and lakehouse platforms and 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 and experience working with US-based stakeholders.
• Experience with AWS S3, Glue, Glue Data Quality, Redshift/Redshift Serverless, Athena, Step Functions, DMS, Lake Formation, and IAM.
• Experience with GCP BigQuery, Cloud Storage, Pub/Sub, Dataflow/Apache Beam, Cloud Composer/Airflow, Dataproc/Spark, Cloud Monitoring, and Cloud Logging.
• Knowledge of advanced Python, PySpark/Apache Spark, ETL/ELT, CDC, batch and streaming processing, event-driven architecture, and data pipeline optimization.

Nice To Haves

• Experience with Dataplex, Data Catalog, and data lineage.

Responsibilities

• Architect and implement scalable enterprise data platforms on GCP, including data lake and lakehouse architectures using Google Cloud Storage and BigQuery.
• Define Bronze, Silver, and Gold/Atomic data layers, ingestion and consumption frameworks, data modeling standards, storage strategies, and multi-tenant or multi-location architectures.
• Lead end-to-end migration of enterprise data platforms from AWS to GCP, including assessment of AWS architecture, pipelines, workloads, dependencies, and operating processes.
• Define the target GCP architecture, migration roadmap, phases, technical dependencies, risks, and rollback strategies; identify opportunities to modernize workloads.
• Map AWS services and workloads to suitable GCP services and prepare technical migration plans.
• Architect real-time pipelines using Pub/Sub, Dataflow/Apache Beam, BigQuery, and Cloud Storage; optimize event ingestion, transformation, delivery guarantees, latency, throughput, scalability, monitoring, and alerting.
• Design and implement batch and real-time ETL/ELT pipelines, CDC patterns, transformation frameworks, and orchestration workflows using Cloud Composer/Airflow.
• Design enterprise data models for analytics and reporting, including dimensional, normalized, denormalized, and multi-tenant models; optimize BigQuery partitioning, clustering, SQL, and query execution.
• Work with BI and Analytics teams to develop scalable data consumption models for batch and real-time workloads.
• Establish data governance, quality, lineage, metadata, ownership, security, and validation standards across the GCP platform.
• Implement appropriate security controls, including IAM, least-privilege access, encryption, service accounts, network security, and data access policies.
• Lead infrastructure automation with Terraform and establish repeatable, secure GCP deployments and CI/CD for data engineering workloads.
• Automate pipeline deployment, testing, and infrastructure provisioning, and establish Dev, QA, UAT, and Production deployment standards.
• Lead performance and cost optimization across BigQuery, Dataflow, Spark, Cloud Storage, streaming, and migrated workloads; develop FinOps strategies and performance benchmarks and SLAs.
• Lead, mentor, and provide technical direction to Data Engineers, Senior Data Engineers, and Technical Leads.
• Conduct architecture and code reviews; establish engineering standards, roadmaps, priorities, and best practices for coding, testing, CI/CD, security, and documentation.
• Break migration requirements into deliverables and track engineering progress, risks, dependencies, and milestones.
• Serve as the primary technical point of contact for US-based stakeholders and collaborate with Business, Product, Data Science, BI, and DevOps teams.
• Translate business requirements into technical solutions, present architecture and migration plans, communicate risks and trade-offs, and collaborate on operational and analytical KPIs.

Benefits

• Flexible remote work environment.
• Continuous learning and certification opportunities.
• Opportunity to lead large-scale AWS-to-GCP cloud transformation initiatives.
• Exposure to enterprise data lakehouse and analytics modernization projects and global enterprise customers.
• Collaborative, innovation-driven engineering culture.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed