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Naveera Technology LLC
Naveera Technology LLC
201 – 500 Darbinieki
KonsultācijasLoģistikaVeselības aprūpe
Naveera Technology LLC ir tehnoloģiju konsultāciju un inženierijas uzņēmums, kas palīdz organizācijām attīstīt mākslīgajā intelektā balstītas spējas, izmantojot praktiskas un ražošanai gatavas sistēmas. Uzņēmuma darbība aptver datu inženieriju, mašīnmācīšanos, ģeneratīvo mākslīgo intelektu, lietotņu izstrādi, mākoņinfrastruktūru un IT operācijas, tostarp datu konveijerus, GenAI modeļu izstrādi, MLOps, kā arī pielāgotas tīmekļa, mobilās un uzņēmumu lietotnes. Naveera atbalsta klientus digitālās veselības aprūpes, finanšu tehnoloģiju, e-komercijas, loģistikas un citās uzņēmējdarbības jomās, izmantojot globālas piegādes komandas, paplašinātu inženiertehnisko atbalstu un izcilības centra modeli, kas vērsts uz datu pārveidošanu noderīgā informācijā un mērogojamās tehnoloģijās.
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Vakances uzņēmumā

Senior Data Engineering Manager, GCP Cloud

Lead AWS-to-GCP migrations and cloud data platform architecture for Naveera Technology’s global engineering clients. Guide teams across governance, streaming, analytics, and cloud modernization.

USAmerikas Savienotās Valstis
120 000 $ – 160 000 $ / gads
AttālinātiPilna slodzeVecākais speciālistsVadošais speciālistsNepieciešamā Valoda: angļuInženierijas vadītājs
AirflowAmazon RedshiftApacheAWSBigQueryETLGoogle Cloud PlatformMākonisPySparkPythonSparkSQLTerraform

Apraksts

  • Build scalable enterprise data platforms on GCP
  • Design data lake and lakehouse architectures with Google Cloud Storage and BigQuery
  • Define Bronze, Silver, and Gold/Atomic data layers
  • Lead enterprise data platform migrations from AWS to GCP
  • Assess AWS architectures, pipelines, workloads, dependencies, and operating processes
  • Set target GCP architecture and migration plans, phases, dependencies, risks, and rollback strategies
  • Lead architecture reviews and technical design discussions
  • Design real-time data pipelines with Pub/Sub, Dataflow/Apache Beam, BigQuery, and Cloud Storage
  • Design high-volume event ingestion, enrichment, and transformation pipelines
  • Develop scalable batch and real-time ETL/ELT pipelines using Python, PySpark, SQL, Dataflow/Apache Beam, BigQuery, and dbt
  • Build orchestration workflows with Cloud Composer/Airflow
  • Design enterprise data models for analytics and reporting
  • Improve BigQuery partitioning, clustering, SQL, and query performance
  • Set standards for data governance, quality, lineage, metadata, ownership, and security
  • Implement IAM, least-privilege access, encryption, service accounts, network security, and data access policies
  • Lead infrastructure automation with Terraform and implement CI/CD pipelines
  • Improve performance and control costs across BigQuery, Dataflow, Spark, Cloud Storage, and streaming workloads
  • Lead and mentor Data Engineers, Senior Data Engineers, and Technical Leads
  • Set technical direction, review architecture and code, and establish roadmaps and engineering priorities
  • Track engineering progress, risks, dependencies, and delivery milestones
  • Serve as the primary technical contact for US-based stakeholders
  • Work with Business, Product, Data Science, BI, and DevOps teams
  • Turn business needs into scalable technical solutions and communicate risks, timelines, and trade-offs

Prasības

  • At least 15 years in data engineering, data architecture, or cloud engineering
  • At least 5 years of hands-on GCP data engineering experience
  • At least 3 years working on AWS-to-GCP migration projects
  • Strong background designing enterprise data lake and lakehouse platforms
  • Experience migrating AWS data workloads to GCP
  • Strong understanding of AWS and GCP service mapping and cloud migration patterns
  • Expert SQL skills and strong Python/PySpark proficiency
  • 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
  • Strong experience with Amazon S3, AWS Glue, AWS Glue Data Quality, Amazon Redshift/Redshift Serverless, Amazon Athena, AWS Step Functions, AWS DMS, AWS Lake Formation, and IAM
  • Strong experience with BigQuery, Google Cloud Storage, Pub/Sub, Dataflow/Apache Beam, Cloud Composer/Airflow, Dataproc/Spark, Cloud Monitoring, Cloud Logging, and Dataplex/Data Catalog
  • Experience with ETL/ELT, CDC, batch and streaming processing, event-driven architecture, and data pipeline optimization

Priekšrocības

  • Flexible remote work
  • Work with global enterprise customers
  • Collaborative engineering culture focused on innovation
  • Ongoing learning and certification opportunities

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