Data Analytics Engineer

Lakeview Loan Servicing•Coral Gables, FL

2d•Remote

About The Position

The Data Analytics Engineer is responsible for designing and maintaining the analytical data structures, semantic models, reporting datasets, and data governance processes that support trusted business intelligence across LHIS. Working within the Business Intelligence function, this role serves as a key owner of data quality, analytical architecture, and reporting enablement across multiple business domains. The Data Analytics Engineer partners closely with Sales, Marketing, Operations, Technology, and Data Engineering to ensure operational processes are structured to support accurate reporting, while developing and maintaining analytical models within Microsoft Fabric. Particular emphasis is placed on sales and customer lifecycle data, ensuring operational systems produce reliable and analytically useful information from the point of collection through final reporting and KPI delivery.

Requirements

Regular sitting and use of hands for handling objects, tools, or controls.
Frequent talking and listening in a moderately noisy environment.
Occasional standing, walking, and reaching with hands and arms.
Rare instances of stooping, kneeling, crouching, or crawling.
Lifting and moving objects up to 10 pounds is a regular part of the role.
Specific vision abilities such as close vision, color vision, and the ability to adjust focus are necessary.
Must connect to the internet via a direct Ethernet connection.
Maintain a dedicated workspace to safeguard customer information.
Internet connection with a minimum download speed of 50 Mbps and a minimum upload speed of 10 Mbps.
If using shared internet, prioritizing the connection for work purposes is strongly recommended, with the preference for a dedicated connection solely for work-related tasks.

Responsibilities

Partner with business leaders to ensure operational processes capture accurate, complete, and reportable data.
Recommend improvements to workflows, field structures, stage definitions, and business processes to improve reporting accuracy and data quality.
Establish and maintain standards for data governance, field usage, and business definitions.
Identify gaps in data collection and implement solutions that improve analytical visibility.
Audit operational data and system usage to ensure consistency across departments.
Serve as the primary analytical stakeholder for business process and data structure decisions, ensuring changes to operational systems support both business execution and future reporting requirements.
Design and maintain semantic models within Microsoft Fabric to support enterprise reporting and analytics.
Develop analytical datasets and business logic required for reporting and performance measurement.
Translate operational business processes into scalable analytical models.
Apply dimensional modeling principles, including Kimball methodologies, fact tables, and dimension tables, to support reporting, dashboarding, and future analytical initiatives.
Partner with Data Engineering to ensure source data is available and properly structured for analytical consumption.
Support the ongoing development and enhancement of the Business Intelligence layer and contribute to scalable reporting frameworks capable of supporting future organizational growth.
Define, document, and maintain KPI calculations and business metric definitions.
Validate reporting outputs against operational expectations and business requirements.
Support dashboard development and ad hoc analytical initiatives for Sales, Marketing, and Operations.
Develop reconciliation processes and data quality controls, including monitoring, validation, and issue resolution, to improve trust in reporting.
Collaborate with stakeholders to ensure reporting solutions support business objectives and improve data capture outcomes.
Identify opportunities for advanced analytics as organizational data maturity increases.