Data, Analytics & AI Engineer ONI

Responsibilities Include but Are Not Limited To:
Data Engineering & Analytics Platform

• Design, build, and maintain reliable, scalable data pipelines using Boomi and Azure Data Factory to integrate data from ERP, EHS, operational, and corporate systems.

• Develop and manage curated data models in Azure SQL and future MS Fabric environment lake house or warehouse architectures to support analytics, AI, and reporting use cases.

• Ensure data quality, consistency, and performance across pipelines, models, and downstream consumers.

• Contribute to data architecture standards, patterns, and best practices as ONI evolves toward Microsoft Fabric.

• Develop and maintain Power BI semantic models, dashboards, and reports that deliver actionable insights to executives and business teams.

• Partner with stakeholders to translate business questions into metrics, KPIs, and analytical solutions.

• Promote self‑service analytics through well‑designed datasets, documentation, and governance.

• Identify, prototype, and deliver AI and machine learning solutions that improve decision‑making, forecasting, anomaly detection, classification, and automation.

• Design and implement agentic workflows that combine data, analytics, and AI models to automate multi‑step business processes, decision support, and operational actions.

• Leverage Azure‑based AI services and emerging Fabric capabilities (e.g., notebooks, ML, real‑time intelligence) to operationalize AI solutions.

• Act as an internal advocate and advisor on responsible AI adoption, helping business units understand practical and strategic AI opportunities.

• Collaborate with IT, security, and Dev Ops teams to ensure solutions align with enterprise standards for security, compliance, and reliability.

• Partner with affiliate companies and cross‑functional ONI teams as a resource on key initiatives.

• Prioritize, scope, and manage data and AI initiatives with clear success metrics and business outcomes.

• Explore, evaluate, and pilot new data, analytics, and AI technologies with a bias toward business value.

• Contribute to a culture of data‑driven decision‑making, experimentation, and continuous improvement across ONI.

• Bachelor’s degree or higher in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related field.

• Strong experience building and supporting data pipelines and system integrations, preferably with Azure Data Factory and/or Boomi.

• Proficiency in SQL and relational data modeling; experience with Azure SQL Database or similar platforms.

• Hands‑on experience developing and maintaining analytics and semantic models using Power BI.

• Programming experience in one or more languages such as Python (including notebooks), with the ability to apply them to data engineering, analytics, and AI use cases.

• Experience applying AI/ML techniques to real‑world business problems, including model development, evaluation, and operationalization.

• Strong analytical thinking, problem‑solving, and attention to detail.

• Ability to communicate complex technical concepts clearly to both technical and non‑technical audiences.

• Self‑driven, curious, and comfortable working in a dynamic, evolving technical environment.

• Experience or strong interest in Microsoft Fabric, including lake house, warehouse, notebooks, real time analytics, and AI workloads.

• Familiarity with agentic AI patterns, workflow orchestration, and automation platforms.

• Experience supporting enterprise data platforms in regulated or security conscious environments.

• Understanding of modern data architecture concepts (ELT, semantic layers, governance, lineage).

• Experience working within large, distributed organizations or multi affiliate environments.

• Strong customer focused mindset with the ability to manage expectations and build trusted partnerships.

• 5 years:
  Applying AI/ML techniques to real world business problems, including model development, evaluation, and operationalization.

• 5 years:
  Programming in one or more languages such as Python (including notebooks), with ability to aply them to data engineering, analytics and AI use cases.

• 5 years:
  Developing and maintaining analytics and semantic models using Power BI

• 5 years:
  Building and supporting data pipelines and system integrations, preferably with Azure Data Factory and/or Boomi.

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