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Naveera Technology LLC
Naveera Technology LLC
201 – 500 Xodimlar
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Naveera Technology LLC tashkilotlarga amaliy va ishlab chiqarishga tayyor tizimlar orqali sun’iy intellektga asoslangan imkoniyatlarni rivojlantirishga yordam beradigan texnologik konsalting va muhandislik kompaniyasidir. Uning faoliyati ma’lumotlar muhandisligi, mashinaviy o‘rganish, generativ sun’iy intellekt, ilovalar ishlab chiqish, bulut infratuzilmasi va IT operatsiyalarini, jumladan ma’lumotlar quvurlari, GenAI modellarini ishlab chiqish, MLOps hamda maxsus veb, mobil va korporativ ilovalarni qamrab oladi. Naveera raqamli sog‘liqni saqlash, fintech, elektron tijorat, logistika va boshqa korporativ sohalardagi mijozlarni global yetkazib berish jamoalari, kengaytirilgan muhandislik ko‘magi va ma’lumotlarni foydali intellekt hamda kengaytiriladigan texnologiyalarga aylantirishga yo‘naltirilgan mukammallik markazi modeli orqali qo‘llab-quvvatlaydi.
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Kompaniyadagi ish o‘rinlari

Senior Data Engineering Manager – GCP, AI/ML & GenAI (US Remote)

Lead AWS-to-GCP data platform migrations and build enterprise AI/ML, GenAI, and MLOps solutions with GCP and Vertex AI. Drive modernization initiatives for a global engineering and IT services partner.

USAmerika Qo‘shma ShtatlariMasofaviyTo‘liq stavkaSeniorYetakchiTalab Qilinadigan Til: inglizchaMuhandislik menejeri
AirflowAmazon RedshiftApacheAWSAzureBigQueryBulutDockerETLFlaskGoogle Cloud PlatformKafkaKubernetesPySparkPythonPyTorchScikit-LearnSparkSQLTensorFlowTerraform

Tavsif

  • Lead enterprise data platform migrations from AWS to GCP
  • Architect scalable GCP data platforms, Data Lakes, and Lakehouses
  • Develop AI/ML, Generative AI, RAG, and MLOps solutions with GCP and Vertex AI
  • Build end-to-end machine learning pipelines for preparation, training, validation, deployment, monitoring, retraining, and lifecycle management
  • Design ingestion, transformation, embedding, indexing, retrieval, batch, streaming, ETL, and ELT pipelines
  • Assess AWS environments and map workloads to equivalent or improved GCP services
  • Create migration roadmaps covering phases, dependencies, risks, rollback plans, and target architectures
  • Design event-driven real-time pipelines with Pub/Sub, Dataflow or Apache Beam, BigQuery, and Cloud Storage
  • Establish enterprise data models, BigQuery partitioning and clustering, and analytics consumption patterns
  • Set standards for data governance, quality, lineage, metadata, security, privacy, access control, and responsible AI
  • Lead Terraform automation, CI/CD, deployment, testing, and environment promotion across Dev, QA, UAT, and Production
  • Improve performance, scalability, latency, throughput, reliability, and cloud costs while defining benchmarks and SLAs
  • Manage and mentor Data Engineers, Senior Data Engineers, and Technical Leads and conduct architecture and code reviews
  • Monitor engineering progress, delivery risks, dependencies, and milestones
  • Act as the primary technical contact for US stakeholders and partner with Business, Product, Data Science, BI, DevOps, Security, and Analytics teams
  • Convert business needs into technical solutions and communicate architecture decisions, migration plans, roadmaps, risks, and trade-offs

Talablar

  • 15+ years of experience in GCP data engineering, data architecture, cloud engineering, AI/ML engineering, or related technology leadership
  • At least 5 years of hands-on GCP data engineering experience
  • At least 3 years of hands-on AI/ML and GenAI experience
  • Demonstrated delivery of AWS-to-GCP migration projects
  • Strong experience designing enterprise Data Lake and Lakehouse platforms on GCP
  • Hands-on expertise with BigQuery, Google Cloud Storage, Dataflow, Pub/Sub, Cloud Composer, Dataproc, IAM, and Terraform
  • Experience moving AWS data workloads, pipelines, and platforms to GCP
  • Strong knowledge of AWS-to-GCP service mapping, migration patterns, modernization, and cloud architecture practices
  • Experience building and deploying AI/ML solutions on GCP with Vertex AI
  • Hands-on experience with Generative AI, LLM applications, RAG, embeddings, vector search, prompt engineering, and enterprise AI assistants
  • Strong MLOps knowledge covering training, model registries, CI/CD/CT, deployment, monitoring, retraining, governance, and rollback
  • Experience delivering secure and responsible AI solutions with privacy, evaluation, access control, auditability, and governance
  • Expert SQL skills with strong Python and PySpark capabilities
  • Strong background in data modeling, warehousing, batch processing, and real-time data engineering
  • Experience with Terraform, Git, GitHub, Cloud Build, CI/CD, and infrastructure automation
  • Experience leading and mentoring data engineering and cross-functional technical teams
  • Strong communication skills and experience working with US-based stakeholders
  • Google Cloud Professional Data Engineer certification preferred
  • Google Cloud Professional Machine Learning Engineer certification preferred
  • Experience with Vertex AI Agent Builder, Vertex AI Search, Gemini on Vertex AI, or enterprise Generative AI platforms preferred
  • Experience with dbt, Apache Airflow, Kafka, Apache Spark, Kubernetes, Cloud Run, and API-driven architectures preferred
  • Experience with Dataplex, Data Catalog, lineage, metadata management, governance, master data management, and data-quality frameworks preferred
  • Experience supporting enterprise or regulated environments with stringent privacy, security, compliance, audit, and governance requirements preferred
  • Technical expertise should include Python, PyTorch, TensorFlow, Scikit-learn, NLP, deep learning, ML algorithms, GenAI, LLMs, GPT, Gemini, Claude, Llama, prompt engineering, fine-tuning, RAG, embeddings, vector databases, semantic and hybrid search, reranking, LangChain, LlamaIndex, LangGraph, Hugging Face, Transformers, AI agents, agentic workflows, tool or function calling, multi-agent systems, MCP, MLflow, Kubeflow, model registries, deployment, monitoring, CI/CD, Vertex AI, Vertex AI Studio, Vertex AI Pipelines, Model Garden, Vector Search, FastAPI, Flask, REST APIs, SQL, Docker, Kubernetes, GCP, AWS, Azure, BigQuery, Dataflow, Spark, Databricks, data lakes, advanced Python, expert SQL, PySpark, Apache Spark, ETL, ELT, CDC, batch and streaming, event-driven architecture, pipeline development and optimization, enterprise Data Lake and Lakehouse, Medallion Architecture, warehousing, data modeling, dimensional modeling, multi-tenant modeling, schema-on-read and schema-on-write, dbt, Apache Airflow or Cloud Composer, Dataproc, Dataflow or Apache Beam, AWS Glue, Redshift, EMR, Lambda, Kinesis, Athena, CloudWatch, GCS, AWS S3, Pub/Sub, Dataplex, Data Catalog, Terraform, Git or GitHub, Cloud Build, CI/CD, Infrastructure as Code, lineage, metadata management, data quality, monitoring, and OpenLineage

Imtiyozlar

  • Flexible remote work
  • Work with customers around the world
  • Collaborate in an innovation-focused environment
  • Access ongoing learning and certification opportunities
  • Lead major AI/ML and GCP innovation initiatives as Head of Engineering

O‘xshash ish o‘rinlari