Senior AI Data Engineer - Data Pipelines & AI Modernization

Accenture PLC; Irving (TX); On-site; USD 120,000 - 210,000; Full time

Benefits offered by this job

Medical benefits

401(k) plan

Bonus opportunities

Paid time off

Job summary

Accenture PLC seeks a seasoned data engineer to lead data-engineering work on migrations feeding AI systems. You will design pipelines and data products, mine git histories for lineage, and apply evidence-extraction techniques to validate sources before mapping is trusted.

Travel may be required; you will collaborate closely with AI teams, ensure data quality and observability, and operate within an agile engineering environment to deliver scalable data solutions.

Qualifications

• Minimum 5 years of hands-on data engineering or data platform engineering, with at least 1–2 years on AI/LLM-related data work.
• Minimum 4 years in agile engineering or consulting teams.
• Minimum 3 years with Python and SQL at production scale, plus at least one cloud data platform.
• Fluency with data lineage and data observability—catching drift before AI drift surfaces.
• Minimum 1 year designing data supply for AI systems—vector stores, embedding pipelines, or agent-facing data products.

Responsibilities

• Lead the data-engineering work on a migration engagement: pipelines and data products feeding AI systems.
• Apply evidence-extraction techniques (dependency analysis, git-history mining) to the source estate before mapping is trusted.
• Travel may be required; amount of travel varies by business needs and client requirements.
• Collaborate with AI teams to ensure data quality, lineage, and observability across data pipelines and AI systems.

Skills

Python

SQL

Data engineering

Data lineage

Data observability

AI/LLM data

Cloud data platform

Git history mining

Education

Bachelor's degree

Equivalent experience

Tools

Kafka

Flink

Vector stores

Embeddings

Job description

Accenture PLC seeks a seasoned data engineer to lead data-engineering work on migrations feeding AI systems. You will design pipelines and data products, mine git histories for lineage, and apply evidence-extraction techniques to validate sources before mapping is trusted.

Travel may be required; you will collaborate closely with AI teams, ensure data quality and observability, and operate within an agile engineering environment to deliver scalable data solutions.