Hybrid BI Data Modeling Engineer - Azure & SQL Expert

Request Technology, LLC

Austin (TX)

Hybrid

USD 120,000 - 160,000

Full time

44 hours ago

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Job summary

Request Technology, LLC is seeking a senior data engineer with 7+ years of experience in data modeling, data warehousing, and ETL. The role focuses on dimensional modeling, data governance, and robust data pipelines using Azure Data Factory and Azure Synapse Analytics.

Collaboration with business units and BI teams will be essential to support enterprise reporting across HR, Finance, and Risk domains. The position offers a hybrid work model with 3 days onsite and 2 days remote, located in

Qualifications

7+ years of experience in data modeling, data warehousing, and ETL processes.
Strong Hands-on experience of dimensional modeling, fact tables, star/snowflake schemas, slowly changing dimensions (SCDs), and tools like Erwin.
Expertise with SQL (including Transact-SQL) and deep experience with relational database systems such as Microsoft SQL Server.
Experience with data pipelines using ETL or ELT techniques and tools such as Azure Data Factory (ADF) to load data into analytics data marts, data warehouses and data lakes.
Experience with analytics data platforms such as Azure Synapse Analytics, OneLake or Microsoft Fabric.
Familiarity with BI platforms such as Microsoft Power BI and Qlik Sense, and experience supporting enterprise reporting.
Exposure to Python, PySpark, Databricks
Understanding of data governance principles, access controls, and data protection
Experience working with operational analytics domains such as HR, Finance, or Risk Management; professional services industry experience is a plus.

Responsibilities

Data Modeling Design: Create and maintain conceptual, logical, and physical data models that support reporting and analytics across enterprise systems.
Business Partnership: Collaborate with stakeholders to translate business needs into scalable data structures and solutions.
ETL Development Support: Contribute to the design of ETL processes to ensure efficient data movement into BI platforms and warehouses.
Data Quality & Validation: Implement checks and rules to ensure data accuracy, consistency, and reliability across systems.
Performance Optimization: Continuously monitor and refine data models and database performance for efficient querying and reporting.
Documentation & Governance: Maintain clear documentation of models, schemas, and data flows while adhering to data governance standards.
Data Security: Help design access controls and security measures to protect sensitive data.
Advanced Querying: Develop and utilize SQL queries for ad hoc analysis, troubleshooting, and data validation.
Agile Collaboration: Participate in Agile workflows across analysis, development, QA, and UAT phases as a data SME.