Senior Data Platform Architect – Lakehouse Engineering

Tata Consultancy Services

Irvine (CA)

Presencial

USD 150 000 - 240 000

Tempo integral

14 dias+
Gerador de candidaturas

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Resumo da oferta

Tata Consultancy Services in Irvine, CA is seeking a Senior Architect – Data Engineering to design, scale, and optimize an enterprise data platform built on Databricks, dbt, and Airflow. You will define blueprints for the data estate, ensure scalable pipelines, and drive governance and cost efficiency.

You will lead data engineers, mentor senior staff, and collaborate with product managers, data scientists, and business leaders to implement end-to-end lakehouse architectures and robust DataOps

Qualificações

  • 15+ years overall experience in IT with data engineering focus.
  • 10+ years in data warehousing and distributed systems.
  • 4+ years architecting production environments in the modern data stack.

Responsabilidades

  • Design end-to-end lakehouse architectures on Databricks; leverage Delta Lake and Unity Catalog.
  • Define blueprints for data estate governance, schema evolution and data security.
  • Mentor senior and mid-level data engineers; lead architecture workshops.
  • Collaborate with product managers, data scientists, and business leaders to solve data gaps.

Conhecimentos

Python (PySpark)
SQL
Technical communication
Leadership
Cross-functional collaboration
Cloud platforms

Formação académica

Bachelor's degree in Computer Science or related field

Ferramentas

Databricks
dbt
Airflow
Terraform

Descrição da oferta de emprego

Tata Consultancy Services in Irvine, CA is seeking a Senior Architect – Data Engineering to design, scale, and optimize an enterprise data platform built on Databricks, dbt, and Airflow. You will define blueprints for the data estate, ensure scalable pipelines, and drive governance and cost efficiency.

You will lead data engineers, mentor senior staff, and collaborate with product managers, data scientists, and business leaders to implement end-to-end lakehouse architectures and robust DataOps

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