Data Engineering Manager – GCP Cloud, AIML

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🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

👮‍♀️ Software Engineering Manager

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Naveera Technology LLC

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201 - 500 employees

💼 Consulting

🏥 Healthcare

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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 a large-scale AWS-to-GCP data platform migration • Architect and implement scalable enterprise data platforms on GCP • Design Data Lake and Lakehouse architectures using Google Cloud Storage and BigQuery • Define Bronze, Silver, and Gold/Atomic data layers • Design batch, real-time, and event-driven ingestion, transformation, and consumption frameworks • Establish standards for data modeling, partitioning, clustering, storage, metadata, lineage, and data access • Analyze and optimize existing AWS data platforms before migration • Map AWS services and workloads to equivalent or improved GCP services • Prepare migration plans, modernization recommendations, technical roadmaps, and implementation plans • Architect real-time pipelines using Pub/Sub, Dataflow, Apache Beam, BigQuery, and Cloud Storage • Design and implement scalable batch and real-time ETL/ELT pipelines on GCP • Develop transformation frameworks using Python, PySpark, SQL, Dataflow, Apache Beam, BigQuery, and dbt • Build orchestration workflows using Cloud Composer and Apache Airflow • Design enterprise data models and optimize BigQuery performance and cost • Design and implement AI/ML and Generative AI solutions on GCP using Vertex AI and related GCP-native services • Build production-grade machine learning pipelines for preparation, training, validation, deployment, monitoring, retraining, and lifecycle management • Develop RAG, enterprise search, document intelligence, AI assistant, summarization, semantic search, embeddings, vector search, and knowledge-management solutions • Implement MLOps practices using Vertex AI Pipelines, Model Registry, Terraform, GitHub, Cloud Build, and CI/CD pipelines • Establish model versioning, experiment tracking, validation, testing, deployment approval, rollback, and environment-promotion standards • Monitor model performance, data drift, latency, reliability, inference cost, response quality, retrieval accuracy, and GenAI risks • Ensure responsible AI, privacy, security, governance, access control, auditability, and human-review processes • Partner with Data Science, Analytics, Product, BI, Security, and US-based stakeholders to deliver AI/ML and GenAI use cases • Act as the primary technical point of contact for US-based stakeholders • Translate business requirements into scalable data, cloud, AI/ML, and Generative AI solutions • Present architecture decisions, migration strategies, roadmaps, implementation plans, risks, timelines, and trade-offs • Communicate delivery status, dependencies, operational risks, and mitigation plans • Collaborate with business teams to define operational, analytical, data-quality, platform, and AI/ML KPIs

🎯 Requirements

• 15+ years of experience in Data Engineering, Data Architecture, Cloud Engineering, AI/ML Engineering, or related technology leadership roles • 5+ years of strong hands-on GCP Data Engineering experience • 1–2 years of relevant experience in AIML Solutioning • Strong hands-on experience with AWS Data Engineering and Data Architecture • Strong experience designing enterprise Data Lake and Lakehouse platforms on GCP • Strong hands-on experience with BigQuery, Google Cloud Storage, Dataflow, Pub/Sub, Cloud Composer, Dataproc, IAM, and Terraform • Experience migrating AWS data workloads, pipelines, and platforms to GCP • Strong knowledge of AWS and GCP service mapping, migration patterns, modernization strategies, and cloud architecture best practices • Experience designing, building, and deploying AI/ML solutions on GCP using Vertex AI • Hands-on experience with Generative AI, LLM-based applications, RAG architectures, embeddings, vector search, prompt engineering, and enterprise AI assistants

🏖️ Benefits

• Medical Insurance • 10 company-paid holidays • Supportive culture with one-of-a-kind growth opportunities • Ability to work from home • Peer-to-peer recognition program

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