Data Engineering Manager — AI & Modernization Lead

Accenture PLC; Seattle (WA); Presencial; USD 101.000 - 270.000; Jornada completa

Descripción de la vacante

Accenture is seeking a data engineer in Seattle to lead modernization efforts, building batch and streaming pipelines and preparing data for AI consumption. You will implement data-plane governance including catalog, quality, lineage, observability to ensure downstream trust.

The role requires hands-on experience in data engineering, AI/LLM projects, and agile teams. Travel may be required up to 100% depending on client needs.

Formación

• Minimum of 5 years hands-on data engineering or data platform engineering, with at least 1–2 years on AI/LLM data work.
• Minimum of 5 years in agile engineering or consulting teams.
• Minimum of 5 years with Python and SQL at production scale, plus at least one cloud data platform.
• Minimum of 5 years with streaming technologies and orchestration tooling (Kafka, Airflow, or equivalent).
• Minimum of 1 year designing for both AI workloads and classical analytics on the same foundation.
• AI-adjacent experience counts toward the bars above: strong credentials in the neighboring discipline combined with 1–2 years of hands-on LLM work is exactly the profile we grow.
• Bachelor's degree or equivalent (minimum 12 years) work experience.

Responsabilidades

• You lead the data-engineering work on a modernization engagement: batch and streaming pipelines, productized data ready for AI consumption, and the data-plane governance — catalog, quality, lineage, observability — that downstream trust stands on

Conocimientos

Data engineering

Agile engineering

Python

SQL

Cloud data platform

AI/LLM data work

Streaming technologies

Educación

Bachelor's degree or equivalent (minimum 12 years) work experience

Herramientas

Kafka

Airflow

Descripción del empleo

Accenture is seeking a data engineer in Seattle to lead modernization efforts, building batch and streaming pipelines and preparing data for AI consumption. You will implement data-plane governance including catalog, quality, lineage, observability to ensure downstream trust.

The role requires hands-on experience in data engineering, AI/LLM projects, and agile teams. Travel may be required up to 100% depending on client needs.