Lead Analytics Engineer – Enterprise Data & AI
Core
Design and implement a unified semantic layer and data modeling strategy to transform enterprise data into clean, AI-ready datasets for intelligent agents and analytical workflows.
Role type
Lead Analytics Engineer (Enterprise Data & AI)
Builds
Unified semantic models, AI-ready datasets, automated testing/observability frameworks
Domain
Enterprise Data Engineering & AI
Deliverable
production ML models | product features
Required skills
Semantic modeling, Data architecture design, Python, SQL, Data orchestration (Airflow, Lakeflow, Argo), AI-generated code review, Enterprise platform schema reconciliation (SAP, Salesforce, Workday), Automated testing frameworks, Data quality assurance
Preferred skills
LLMs for data reconciliation/anomaly detection, Query optimization for massive datasets, Self-service analytics environment creation (Tableau, Streamlit)
Technologies
Python, SQL, Airflow, Lakeflow, Argo, Snowflake, Databricks, Big Query, SAP S/4HANA, Salesforce, Workday, Anaplab, Tableau, Streamlit
Responsibilities
Design and maintain a unified semantic model for cross-functional stakeholders and AI Agents; Collaborate with Data & AI Engineers to optimize data for high-accuracy, low-latency queries; Establish organizational standards for data modeling, version control, testing, and documentation; Implement automated testing and observability frameworks for pipeline reliability; Partner with business leaders to translate operational requirements into scalable data solutions
Seniority
Senior, hands-on IC with leadership responsibilities
