Analytics Engineer Direct Hire Hybrid

DEXTER TECHNOLOGIES INC•Houston, TX

1d•Hybrid

About The Position

This hybrid role bridges data engineering and business intelligence, combining SQL development and optimization with Power BI semantic modeling and reporting. The Analytics Engineer will build staging tables, views, and fact/dimension models; maintain semantic models and reports; and monitor scheduled data pipelines, providing first-line troubleshooting when failures occur. The role works closely with the Sr. Manager, Data & Analytics and business stakeholders across Finance, Operations, and other functions to deliver accurate, well-modeled data. It offers broad ownership across the data stack on a small team. The position uses an Azure SQL data warehouse, Azure Data Factory, and Power BI. It also involves translating business rules and reporting requests into documented data models, maintaining data lineage and metric definitions, following and evolving team standards, and identifying opportunities to improve data workflows and analytics capabilities.

Requirements

At least 3 years in a data-focused role such as analytics engineer, BI developer, or data analyst, with hands-on SQL experience.
Comfort with SQL CTEs, window functions, and reading and writing complex, multi-source views.
Solid Power BI experience, including building semantic models from scratch and writing DAX involving CALCULATE, filter context, and context transition.
Fundamentals of dimensional modeling, including star schemas and slowly changing dimensions.
Experience working directly with business stakeholders to translate ambiguous requirements or business rules into a working data model.
Strong attention to data integrity, including checking joins and date boundaries.
Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.

Nice To Haves

Exposure to an ERP or other core business system as a data source, such as order, invoicing, or general ledger data.
Understanding of ETL/ELT concepts and working knowledge of orchestration tools such as Azure Data Factory or similar pipeline automation tools.
Familiarity with Microsoft Fabric administration and environment, including Lakehouses and Dataflows Gen2.
Basic Git or source control experience.
Python for data tasks.
Knowledge of data quality frameworks and data governance practices.
Master's degree.

Responsibilities

Design, build, and maintain SQL views, staging tables, and fact/dimension models in the Azure SQL data warehouse, including deduplication and business-rule logic.
Build and maintain Power BI semantic models, relationships, DAX measures, security roles, reports, and dashboards for business stakeholders and company-wide reporting.
Share responsibility with the Sr. Manager, Data & Analytics for monitoring scheduled Azure Data Factory pipelines and Power BI dataset refreshes; respond to failures and perform basic troubleshooting.
Make minor modifications to existing pipelines to support new or changing business requirements as familiarity with the tooling grows.
Partner with business subject-matter experts to translate reporting requests and business logic into accurate, well-documented data models.
Write and maintain documentation for data models, metric definitions, and report logic so data lineage and ownership are clear.
Follow and help evolve team standards for naming conventions, DAX style, and semantic model design.
Identify process improvements, optimize data workflows, and incorporate new technologies or tools to enhance data analytics capabilities.