BI Data Analyst II

Service Corporation International•Houston, TX

2d•Onsite

About The Position

Our associates celebrate lives. We celebrate our associates. This role is responsible for building and managing end-to-end ETL/ELT workflows, designing and developing data integration and transformation solutions using Azure Synapse Analytics Pipelines, and creating and maintaining data models, datasets, and reporting solutions using Power BI. The position involves designing interactive dashboards, reports, and visualizations to support business intelligence and decision-making, managing data refresh schedules, report deployments, and security configurations within Power BI. Collaboration with business stakeholders to gather reporting and analytics requirements is key. The role also includes developing and implementing dimensional data models, performing data analysis and profiling, and leveraging Artificial Intelligence (AI) and Machine Learning (ML) technologies for advanced analytics and predictive modeling. Evaluating emerging AI, Generative AI, and cloud-based analytics technologies for innovation and implementing AI-powered solutions for data quality, anomaly detection, forecasting, and automation are also part of the responsibilities.

Requirements

Bachelor’s degree in computer science, Information Systems, Engineering, Business Analytics, Data Science, or a related field.
Five (5) years of Information Technology experience with a strong focus on data integration, data warehousing, business intelligence, and analytics solutions.
Three (3) years of hands-on experience developing and maintaining Azure Synapse Analytics Pipelines.
Experience integrating data from multiple sources, including cloud and on-premises systems.
Three (3) years of experience designing, developing, and supporting Power BI dashboards, reports, and datasets.
Strong experience in data modeling, dimensional modeling, and data transformation techniques.
Experience developing and optimizing SQL queries, stored procedures, database objects, and SQL Server solutions.
Experience implementing data quality, validation, and governance processes.
Experience managing Power BI workspaces, datasets, gateways, row-level security (RLS), and report deployment processes.
Experience collaborating with business users, data analysts, data scientists, and technical teams to deliver reporting, analytics, and AI-driven solutions.

Nice To Haves

Experience supporting AI/ML initiatives through data engineering, data preparation, and analytics platforms is preferred.
Knowledge of Azure AI services, cloud analytics platforms, and modern data architecture patterns is desirable.

Responsibilities

Build and manage end-to-end ETL/ELT workflows for ingesting, transforming, and loading data from multiple sources.
Design, develop, and maintain scalable data integration and transformation solutions using Azure Synapse Analytics Pipelines.
Develop, optimize, and monitor data pipelines to ensure data quality, reliability, and performance.
Create and maintain data models, datasets, and reporting solutions using Power BI.
Design interactive dashboards, reports, and visualizations to support business intelligence and decision-making.
Manage data refresh schedules, report deployments, and security configurations within Power BI.
Collaborate with business stakeholders to gather reporting and analytics requirements.
Develop and implement dimensional data models, including star and snowflake schemas, to support data warehousing and business intelligence initiatives.
Perform data analysis and data profiling to identify data quality issues and improve data integrity across systems.
Leverage Artificial Intelligence (AI) and Machine Learning (ML) technologies to support advanced analytics, predictive modeling, and business insights.
Collaborate with data scientists, business analysts, and stakeholders to integrate AI-driven solutions into enterprise reporting and decision-making processes.
Evaluate emerging AI, Generative AI, and cloud-based analytics technologies to identify opportunities for innovation and process improvement.
Implement AI-powered data quality, anomaly detection, forecasting, and automation solutions to enhance business operations and reporting capabilities.