GCP Data Engineering Manager

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Naveera Technology LLC

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

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 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 target-state GCP architecture, migration roadmap, phases, dependencies, risks and rollback strategies • Lead architecture reviews and technical design discussions • Architect and implement scalable enterprise GCP data platforms, Data Lake and Lakehouse architectures • Design batch and real-time ETL/ELT, streaming ingestion, transformation and consumption frameworks • Design BigQuery data models, partitioning, clustering and scalable analytics consumption models • Establish data governance, data quality, lineage, metadata, ownership and security standards • Lead Terraform-based infrastructure automation and CI/CD deployment practices • Optimize GCP performance, scalability, SLAs and cloud costs • Lead, mentor and provide technical direction to Data Engineers, Senior Data Engineers and Technical Leads • Track engineering progress, risks, dependencies and delivery milestones • Act as primary technical point of contact for US-based stakeholders • Collaborate with Business, Product, Data Science, BI and DevOps teams • Translate business requirements into scalable technical solutions and communicate architecture decisions, risks, timelines and trade-offs

🎯 Requirements

• 15+ years of experience in Data Engineering, Data Architecture or Cloud Engineering • 5+ years of hands-on GCP Data Engineering experience • Strong hands-on experience with AWS Data Engineering and Architecture • Proven experience working on AWS-to-GCP migration projects • Strong experience designing enterprise Data Lake / Lakehouse platforms • 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 • Ability to assess AWS workloads, define GCP target architecture and lead migration through production implementation • Expertise in BigQuery, Google Cloud Storage, Pub/Sub, Dataflow / Apache Beam, Cloud Composer / Airflow, Dataproc / Spark, Cloud Monitoring and Cloud Logging • Knowledge of AWS S3, Glue, Glue Data Quality, Redshift, Athena, Step Functions, DMS, Lake Formation and IAM • Experience with ETL/ELT, CDC, batch and streaming data processing and event-driven architecture • Experience with Data Lakehouse, Medallion Architecture, dimensional and multi-tenant data modeling • Knowledge of schema-on-read, schema-on-write, data lineage, metadata management and data governance • Experience with dbt, Terraform, Git/GitHub, Cloud Build, CI/CD, data quality frameworks and OpenLineage • Hands-on GCP Engineering Manager experience preferred; current Senior/Lead Data Engineer profiles are not suitable

🏖️ Benefits

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