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TTEC Digital
TTEC Digital
1001 – 5000 Darbinieki
H1B vīzas sponsorsKonsultācijasMākslīgais intelektsMārketings
TTEC Digital palīdz organizācijām uzlabot klientu pieredzi, izmantojot konsultācijas, mārketingu, mākslīgo intelektu un klientu tehnoloģijas. Uzņēmuma darbība aptver mākslīgo intelektu, kontaktu centru tehnoloģijas, klientu attiecību pārvaldību, datu analīzi, klientu pieredzes stratēģiju un dizainu, kā arī pārvaldītus pakalpojumus. Risinājumi ir paredzēti vidēja lieluma uzņēmumu digitālās pārveides atbalstam un efektīvākai saziņai ar klientiem.
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Vakances uzņēmumā

Senior Data Engineer, Data and AI - TTEC Digital (Texas Remote)

Lead Azure and Databricks data platform architecture for TTEC Digital’s customer-experience solutions. Build governed pipelines, APIs, and AI integrations while guiding engineering teams.

USAmerikas Savienotās ValstisTXTeksasa
155 000 $ – 175 000 $ / gads
AttālinātiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuDatu inženieris
AzurePySparkPythonSQLUnity

Apraksts

  • Lead end-to-end data platform development across ingestion, preparation, transformation, analytics, and activation.
  • Architect Bronze, Silver, and Gold Medallion lakehouse patterns with OneLake and Delta Lake.
  • Own dimensional, normalized, and semantic data modeling for client engagements.
  • Create batch and streaming ingestion using Fabric Data Factory, Azure Databricks Structured Streaming, and event-driven services such as Event Hubs.
  • Reduce architectural risk and technical debt while improving pipeline performance and cost efficiency.
  • Develop APIs and data services that enable governed data activation.
  • Build MCP and API integrations linking business systems, Data Agents, and agentic AI interfaces.
  • Work with AI and Architecture teams to make enterprise data available to Data Agents and generative AI applications.
  • Apply governance practices with Microsoft Purview and/or Unity Catalog.
  • Support production operations and incident response for critical pipelines and activation services.
  • Mentor Data Engineers through code, model, and architecture reviews while providing technical direction.
  • Advise client stakeholders on architectural trade-offs and design decisions.
  • Help develop reusable frameworks, accelerators, and engineering standards.
  • Contribute to presales work, including estimates, proposals, and solution design.
  • Assess new Microsoft Fabric and Azure Databricks capabilities for client platforms.

Prasības

  • Bachelor’s or master’s degree in computer science, engineering, mathematics, statistics, or a related technical field.
  • Five to eight years of data engineering experience, including ownership of production Azure data pipelines.
  • Expertise in Python, SQL, and PySpark for developing distributed data pipelines at scale.
  • Extensive hands-on experience with Azure Data and AI technologies, including Azure Data Factory, Microsoft Fabric, Synapse, ADLS Gen2, and/or Azure Databricks with Delta Lake, OneLake, and Medallion patterns.
  • Strong experience in data modeling, schema design, and enterprise data architecture across ingestion through activation.
  • Experience creating APIs and MCP integrations for front-line systems, Data Agents, and other agentic AI interfaces.
  • Experience with orchestration and CI/CD tools such as Fabric pipelines, Azure Data Factory, Databricks Workflows, and Azure DevOps.
  • Strong understanding of data governance and security tools, including Microsoft Purview and/or Unity Catalog.
  • Proven ability to mentor engineers and lead technical design discussions in client-facing environments.
  • Strong independent troubleshooting and problem-solving skills for complex, large-scale data issues.
  • Excellent communication skills for explaining technical trade-offs to engineering and client audiences.
  • Microsoft certifications such as Azure Data Engineer Associate or Fabric Analytics Engineer Associate and/or Databricks certifications are preferred.

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AttālinātiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuDatu inženieris
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