Job Description
Local candidates only please. No sponsorship available at this time. Thank you!
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We are seeking a Lead Data & AI Engineer to design, build, and advance enterprise data and AI capabilities across a global organization. This role will play a key part in developing a modern, cloud-based data platform and implementing practical AI solutions that improve business intelligence, operational efficiency, and decision-making across the organization.
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The ideal candidate is a hands-on technical leader who can move between data architecture, engineering, analytics, and applied AI, translating business needs into scalable technical solutions.
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Key Responsibilities
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- Data Engineering & Architecture: Design and build a modern, cloud-native enterprise data lake and data platform, integrating data from ERP, CRM, supply chain, financial, and other business systems.
- Data Pipelines & Integration: Develop scalable batch and real-time data pipelines, ETL/ELT processes, data models, and integrations across multiple enterprise data sources.
- AI & Machine Learning: Develop and implement AI/ML solutions, including predictive analytics, forecasting, anomaly detection, intelligent automation, and generative AI applications.
- Generative AI & AI Agents: Build and deploy LLM-powered applications, RAG solutions, conversational AI assistants, and intelligent agents that connect to enterprise data and automate business workflows.
- Business Intelligence & Analytics: Develop enterprise reporting, dashboards, semantic data models, and self-service analytics capabilities using tools such as Power BI, Tableau, or similar platforms.
- Data Governance & Quality: Establish data quality standards, metadata management, data lineage, master data practices, and appropriate security and access controls.
- Business Collaboration: Work directly with stakeholders across Finance, Sales, Marketing, Operations, Supply Chain, and other functions to identify opportunities and deliver data and AI solutions with measurable business value.
- Technical Leadership: Establish engineering standards and best practices, evaluate emerging technologies, and provide technical guidance across data engineering, analytics, and AI initiatives.
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Required Qualifications
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- 8+ years of experience in data engineering, data architecture, analytics, AI/ML engineering, or a related discipline.
- Strong hands-on experience designing and building enterprise data platforms, data lakes, data warehouses, and scalable data pipelines.
- Experience with one or more major cloud platforms: Azure, AWS, or GCP.
- Strong SQL and Python development skills.
- Practical experience developing and deploying AI/ML solutions, including generative AI, LLMs, RAG, predictive modeling, and AI-powered automation.
- Experience with modern data and analytics technologies such as Snowflake, Databricks, Microsoft Fabric, BigQuery, Power BI, Tableau, or similar platforms.
- Experience integrating data from enterprise applications such as SAP, Microsoft Dynamics, Salesforce, and other ERP/CRM systems.
- Understanding of data governance, data quality, master data management, and enterprise data security.
- Ability to work directly with business stakeholders, understand operational challenges, and translate requirements into technical solutions.
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