The Role
Design and deliver scalable Microsoft Fabric data and AI solutions, including Lakehouse architectures, ingestion pipelines, medallion layers, semantic models, DAX measures, AI Agents, Data Agents, ontologies, and RAG experiences. Develop production transformations with Python, PySpark, and SQL; integrate AI capabilities into applications and APIs; and collaborate across technical and business teams. The role also emphasizes governance, testing, documentation, DevOps automation, security, and responsible AI practices.
Summary Generated by Built In
Role overview
Join the Fabric Center of Excellence to design and deliver modern data and AI solutions on Microsoft Fabric. The role combines data engineering, semantic modeling and Agentic AI to build scalable data products, AI Agents, Data Agents, ontologies and business-facing applications.
Key responsibilities- Design and develop scalable data engineering solutions using Microsoft Fabric Lakehouse, Data Factory, pipelines and notebooks.
- Build ingestion, transformation and medallion-layer patterns for reliable, reusable and governed data products.
- Design and develop AI Agents, Data Agents, ontology-driven solutions and Retrieval-Augmented Generation (RAG) experiences.
- Create high-quality semantic models, relationships, calculations and DAX measures for analytics and AI consumption.
- Use Python, PySpark and SQL to develop production-grade transformations, orchestration and validation logic.
- Apply Semantic Link Labs and Fabric Notebooks to automate semantic-model engineering, testing, documentation and operational tasks.
- Integrate data and AI capabilities into web applications, APIs and business workflows.
- Collaborate with architects, platform engineers, product owners and business stakeholders from discovery through production deployment.
- Contribute to engineering standards, reusable accelerators, technical documentation and knowledge sharing across the CoE.
- Strong Microsoft Fabric data engineering experience across Lakehouse, pipelines, notebooks and OneLake.
- Python, PySpark and advanced SQL for data processing and transformation.
- Semantic modeling, DAX, dimensional modeling and performance optimization.
- Knowledge of Agentic AI frameworks, RAG patterns, embeddings, vector search and LLM integration.
- Hands-on understanding of AI Agents, Data Agents, ontology concepts and AI-ready semantic models.
- Working knowledge of Snowflake and Databricks.
- Git, CI/CD, REST APIs, security fundamentals and production deployment practices.
POSITION 02 | CONTINUED
Qualifications and certifications- Bachelor’s degree in computer science, data engineering, artificial intelligence or a related discipline, or equivalent relevant experience.
- Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) is mandatory.
- Related certifications such as DP-203, AI-102 or PL-300 are preferred.
- 3-5 years of relevant experience in data engineering, analytics engineering or AI solution development.
- Developing AI-enabled web applications, APIs or conversational analytics experiences.
- Azure AI services, Azure OpenAI or comparable enterprise LLM platforms.
- Production implementation of RAG or Agentic AI solutions with evaluation, observability and responsible AI controls.
- Databricks, Snowflake, Delta Lake and modern cloud data-platform integration.
- Direct Lake, real-time analytics, deployment pipelines and DevOps automation.
- Strong engineering discipline and an experimentation mindset.
- Ability to translate business problems into scalable data and AI solutions.
- Clear communication, collaborative delivery and practical documentation.
- Commitment to security, governance, responsible AI and measurable business outcomes.
- Reusable and production-ready Fabric data products.
- Trusted semantic and ontology layers that improve analytics and AI quality.
- Secure, useful AI Agents and Data Agents aligned with business requirements.
- Faster delivery through automation, standards and shared engineering patterns.
Skills Required
- Bachelor's degree in computer science, data engineering, artificial intelligence, or a related discipline, or equivalent relevant experience
- 3-5 years of relevant experience in data engineering, analytics engineering, or AI solution development
- Strong Microsoft Fabric data engineering experience across Lakehouse, pipelines, notebooks, and OneLake
- Python, PySpark, and advanced SQL for data processing and transformation
- Semantic modeling, DAX, dimensional modeling, and performance optimization
- Knowledge of Agentic AI frameworks, RAG patterns, embeddings, vector search, and LLM integration
- Hands-on understanding of AI Agents, Data Agents, ontology concepts, and AI-ready semantic models
- Working knowledge of Snowflake and Databricks
- Git, CI/CD, REST APIs, security fundamentals, and production deployment practices
- Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
- DP-203, AI-102, or PL-300 certification
- Experience developing AI-enabled web applications, APIs, or conversational analytics experiences
- Experience with Azure AI services, Azure OpenAI, or comparable enterprise LLM platforms
- Production implementation of RAG or Agentic AI solutions with evaluation, observability, and responsible AI controls
- Experience with Databricks, Snowflake, Delta Lake, and modern cloud data-platform integration
- Experience with Direct Lake, real-time analytics, deployment pipelines, and DevOps automation
Ecolab Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Ecolab and has not been reviewed or approved by Ecolab.
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Retirement Support — Feedback suggests the company provides strong retirement programs, including a 401(k) with employer matching and a pension, alongside options like an employee stock purchase plan. Offerings such as retiree healthcare benefits and diverse investment choices reinforce long-term financial support.
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Healthcare Strength — Feedback suggests medical coverage is broad, with HSA plan options and company contributions, prescription benefits, dental and vision, and virtual care and mental health support. Company-paid wellness programs and income protection (short- and long-term disability, life and accident) further strengthen core coverage.
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Parental & Family Support — Family-focused programs include fertility support, adoption assistance, and paid parental leave, complemented by counseling and resource services. These offerings are positioned as supportive of employee well-being across different life stages.
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The Company
What We Do
A trusted partner at nearly three million customer locations, Ecolab (ECL) is the global leader in water, hygiene and infection prevention solutions and services. With annual sales of $12 billion and more than 44,000 associates, Ecolab delivers comprehensive solutions, data-driven insights and personalized service to advance food safety, maintain clean and safe environments, optimize water and energy use, and improve operational efficiencies and sustainability for customers in the food, healthcare, hospitality and industrial markets in more than 170 countries around the world. For more Ecolab news and information, visit www.ecolab.com, or follow us on twitter.com/ecolab, facebook.com/ecolab or instagram.com/ecolab_inc.
