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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Enterprise Data & Analytics Strategist - **Company:** Wright Technical Services - **Location:** Columbus, OH, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Computer Vision, Cloud Computing, Information Systems, Data Governance, Extract Transform Load (ETL), IBM Cognos Business Intelligence, Python (Programming Language), Machine Learning, SAP ERP, Natural Language Processing, Power BI, SAP NetWeaver Business Warehouse, SAP NetWeaver Data Management, Enterprise Data Management, Azure Data Factory, Generative AI, AI Platforms, Information Technology, Data Analytics, Qlikview, Tools for Reporting, Data Pipelines, Programming Languages - **Published:** June 13, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d7411abafd8a203f ## About the Role Do you have experience in Stakeholder relationship building?, Do you have a Bachelor's degree?, * Bachelor's degree in Data Analytics, Computer Science, Information Systems, or a related discipline required. * Minimum of 7 years of progressive experience in data analytics, business intelligence, or related fields. * Demonstrated experience developing and implementing enterprise analytics strategies. * Minimum of 5 years managing third-party resources, including offshore delivery teams. * Experience deploying AI/ML solutions in a business environment. * Advanced knowledge of reporting platforms including Incorta, Power BI, Qlik, Cognos, and SAP BW. * Strong expertise in ETL tools and enterprise data pipeline development. * In-depth knowledge of SAP ECC table structures and SAP data modeling. * Proficiency in Python, R, or similar programming languages for machine learning and data science. * Working knowledge of generative AI, natural language processing (NLP), and computer vision applications. * Experience with Azure Data Services and cloud-based analytics environments preferred. * Strategic thinker with the ability to translate business strategy into data-driven execution. * Strong leadership and stakeholder engagement skills. * Ability to operate effectively in a hands-on, individual contributor capacity. * High level of accountability and execution discipline. * Excellent written and verbal communication skills. ## Description Wright Technical Services is proud to represent a Performance Materials global leader in the plastics industry for this position. The Data & Analytics Manager is responsible for leading enterprise analytics and artificial intelligence strategy. This is a hands-on individual contributor role with full ownership of the analytics and AI vision, roadmap, and execution oversight. The role designs, builds, and delivers scalable data and AI solutions that drive business performance and operational excellence. While strategic direction and technical architecture are owned internally, delivery execution is supported through third-party onshore and offshore resources managed by this position. This role requires a balance of strategic leadership, technical depth, and strong stakeholder engagement to translate business requirements into high-impact analytics and AI solutions., The responsibilities of the position include, but are not limited to, the following: * Architect, design, and oversee the development and deployment of analytics solutions across platforms including Incorta, Azure Data Services, SAP ECC, SAP BW, Power BI, Qlik, and Cognos. * Collaborate with business stakeholders to gather requirements and translate business needs into scalable technical solutions. * Lead enterprise reporting, data modeling, and visualization efforts to deliver high-quality, actionable insights. * Establish and enforce data governance, quality standards, security protocols, and compliance practices across analytics platforms. * Drive enterprise adoption of self-service analytics and improve organizational data literacy. * Monitor KPIs and performance metrics to support strategic and operational initiatives. * Continuously enhance analytics maturity across the organization. * Develop and deploy AI/ML models to enable predictive analytics, process automation, and decision intelligence. * Evaluate and implement AI platforms, tools, and frameworks aligned with enterprise strategy. * Identify and prioritize AI use cases in collaboration with cross-functional business teams. * Lead proof-of-concept initiatives and transition validated models into production environments. * Stay current on AI advancements, regulatory considerations, and responsible AI practices. * Manage and direct third-party onshore and offshore analytics resources. * Ensure alignment of delivery timelines, quality standards, and business objectives. * Provide technical guidance and oversight to internal and external analytics contributors. ## Related Videos - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Headless by Design: Building Enterprise Systems That Agents Can Actually Use](https://www.wearedevelopers.com/videos/100092-headless-by-design-building-enterprise-systems-that-agents-can-actually-use) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)