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Ecolab

Provides water, hygiene, infection prevention solutions

Microsoft Fabric Data Engineer - Fabric Center of Excellence

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • Strong Microsoft Fabric data engineering experience across Lakehouse, pipelines, notebooks and OneLake.
  • Python, PySpark and advanced SQL for data processing and transformation.
  • Experience with semantic modeling, DAX, dimensional modeling and performance optimization.
  • Knowledge of Agentic AI frameworks, Retrieval-Augmented Generation patterns, embeddings, vector search and large language model integration.
  • Hands-on understanding of AI Agents, Data Agents, ontology concepts and AI-ready semantic models.
  • Working knowledge of Snowflake and Databricks.
  • Experience with Git, continuous integration and continuous delivery, REST APIs, security fundamentals and production deployment practices.
  • 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) certification.
  • Three to five years of relevant experience in data engineering, analytics engineering or AI solution development.
  • Ability to translate business problems into scalable data and AI solutions.
  • Commitment to security, governance, responsible AI and measurable business outcomes.

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 experiences.
  • Create 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 Center of Excellence.

Desired Qualifications

  • Related certifications such as DP-203, AI-102 or PL-300.
  • Experience developing AI-enabled web applications, APIs or conversational analytics experiences.
  • Experience with Azure AI services, Azure OpenAI or comparable enterprise large language model platforms.
  • Production implementation of Retrieval-Augmented Generation 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.

About the Company

Ecolab

Provides water, hygiene, infection prevention solutions

Ecolab provides water, hygiene and infection prevention solutions and services to about three million commercial locations in more than 170 countries. It combines cleaning, sanitizing, disinfection, and water-treatment products with on-site service and data-driven insights to help customers improve safety, cleanliness, and efficiency. Its global scale and breadth across food, healthcare, hospitality and industrial markets, plus a large field service network, differentiate it as an integrated partner rather than a one-off supplier. Its goal is to help customers run safer, cleaner operations while using water and energy more efficiently and reducing environmental impact.

Company size
10,001+
Company stage
IPO
Headquarters
St Paul, MN
Founded
1923

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