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Lead Data Engineer, AI & Modernization

L7

accentureAustin, TXtoday
Overview: In this role you lead data-engineering efforts for a migration engagement, building pipelines and data products that feed AI systems. You apply evidence-based techniques to the source estate before mapping, using data lineage and observability to ensure trust in the data. You’ll collaborate with cross-functional teams in an agile setting to enable AI-driven outcomes. This is a hands-on, problem-solving role at scale that intersects data engineering with AI/LLM initiatives. You’ll work in a mission-driven environment that values practical archaeology-like data discovery and impact. Compensation / Benefits medical dental vision 401(k) bonus opportunities paid time off
Responsibilities: Lead data-engineering work on migration engagements, delivering pipelines and data products for AI systems Apply evidence-extraction techniques (dependency analysis, git-history mining) before data mapping Develop and maintain data pipelines feeding AI models and data products Design and implement data lineage and observability to detect data drift early Collaborate with agile teams to deliver production-grade data solutions Contribute to data architecture decisions and engineering best practices
Key requirements: 5+ years of hands-on data engineering or data platform engineering 1–2 years of AI/LLM-related data work 4+ years in agile engineering or consulting environments 3+ years with Python and SQL at production scale Experience with at least one cloud data platform Knowledge of data lineage and data observability 1+ year designing data supply for AI systems (vector stores, embedding pipelines, or agent-facing data products) Bachelor's degree or equivalent (minimum 12 years) work experience collaborative team player analytical problem-solver effective communication in an agile setting Python SQL data pipelines
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Level

ManagerL7

Location

Austin, TX

Occupation

Data Warehousing Specialists

Industry

Computer Systems Design Services

Posted

today

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