Cloud Data Engineer

Omni Hotels & ResortsDallas, TX
Onsite

About The Position

Omni Hotels and Resorts creates genuine, authentic guest experiences at over 50 distinctive luxury hotels and resorts in leading business gateways and leisure destinations across North America. Omni Hotels is known for its exemplary culture, authenticity to the markets in which we operate, innovation and exceptional service. Our commitment to career development has created tenure and loyalty that enables us to perpetuate our family atmosphere. Omni’s Cloud Data Engineer specializing in Microsoft Fabric is responsible for designing, building, and managing end-to-end data pipelines within the unified Microsoft Fabric SaaS environment. They will focus on ingesting, transforming, and storing data in a Lakehouse or Warehouse architecture, ensuring high performance, data quality, and security using tools like Spark/Python Notebooks for API data sources, Fabric Pipeline.

Requirements

  • Must have 4 Year bachelor’s degree in Computer Science, Engineering, Statistics, or related field.
  • Preferred Five Year experience or 3 Year with Master’s.
  • Must have worked with Azure cloud services for at least 2 years.
  • Must have worked with any of the RDBMS in the past with minimum two from DB2, Informix, SQL Server, MySQL, Oracle, Postgres, Maria DB.
  • Must have Python experience in data profiling and data manipulation against Database and API data sources.
  • Intermediate level of programming skills in Python and SQL, stored procedures.
  • 4-to-5-year Experience in Python, SQL, CI/CD and/or extensive use in the delivered projects.
  • Previous proven work with Fabric pipeline workflow or Azure ADF.
  • Experience with REST APIs, GraphQL APIs and gRPC API for data integration, web protocol as data delivery platform.
  • Knowledge of both Windows and Linux VM consoles with PowerShell and Linux Bash scripts.
  • Source Control Experience with GIT, SVN, Bitbucket or Azure DevOps.

Nice To Haves

  • Worked with data related to Hospitality Industry or Financial Industry for Revenue Management, Sales, and/or Digital Marketing
  • Worked with LLMs and Ai Agent Workflow.

Responsibilities

  • Contribute to Omni’s Modern data platform with Design and automate scalable ETL/ELT data pipelines using Microsoft Fabric Pipeline and Notebooks using the existing Dynamic metadata driven architecture.
  • Participate in assessing source systems creating metadata mappings and write pipeline that will be used to support insights, analytics, reporting and future data products required to drive profitable growth for the business.
  • Collaborate with business leaders, subject matter experts, and decision-makers to develop scope of work, success criteria and create new data streams and optimize existing pipelines.
  • Work with different source systems storage models both in cloud and on premises to evaluate underlying schemas, datasets and produce pipeline rule engine.
  • Demonstrate a good understanding of data de-duping, data wrangling and data profiling using Python.
  • Scope and/or evaluating the scope of work for each subject area requirements.
  • Build data quality checks, automated testing, and monitoring into solution delivery
  • Use structured decision-making and following project timelines to complete projects
  • Dev and Prod environments to maintain, deploy and monitor metadata driven ETL Models in production
  • Design and maintain scalable data pipelines and "Medallion" architectures using PySpark, SQL, and Fabric Notebooks to transform raw data into analytics-ready star schemas and semantic models.
  • Optimize Spark jobs and SQL queries for peak capacity performance while implementing enterprise-grade security via RBAC, sensitivity labeling, and Microsoft Purview.
  • Drive advanced analytics through the integration of Knowledge Graphs, Ontology, and AI Agents using Fabric Data Agents or AI Foundry.
  • Work with technical staff such as data analyst/scientist to assist in the design of their deliverables
  • Collaborate with the offshore support of the system.
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