Data Engineer - SQL

This role is onsite in Ocala, Florida

Develop, maintain, monitor, and optimize data pipelines that move information from operational business systems into the company’s enterprise data platform and data lake.

Design and maintain ETL and ELT processes using Azure Data Factory and related Azure data technologies.

Manage and support the company’s Azure Data Lake environment, including data organization, storage structures, processing workflows, access, and overall platform reliability.

Architect new data feeds and integrations from enterprise applications, APIs, databases, files, and other internal and external data sources.

Develop processes for ingesting structured and semi-structured data including SQL data, APIs, JSON, CSV, flat files, and other common data formats.

Troubleshoot data feed failures, pipeline errors, processing issues, data discrepancies, and other problems affecting the availability or accuracy of business data.

Monitor and improve data pipeline performance, processing times, query performance, resource utilization, and overall data platform efficiency.

Develop and maintain SQL queries, views, stored procedures, transformations, and reusable data structures used by reporting and business applications.

Develop curated datasets and reporting views that provide Power BI and other analytics tools with consistent, reliable, and understandable business data.

Work with Power BI developers and data analysts to understand reporting requirements and translate business needs into appropriate data structures and models.

Design and maintain data models that support enterprise reporting, analytics, operational reporting, historical analysis, and KPI measurement.

Apply dimensional modeling principles where appropriate, including fact tables, dimension tables, relationships, measures, historical data, and common business entities.

Improve business visibility into data by identifying opportunities to make information easier to access, understand, analyze, and use for decision-making.

Establish and maintain appropriate data quality controls, validation processes, reconciliation procedures, and monitoring to identify missing, inaccurate, duplicated, or inconsistent data.

Develop processes for incremental data loading, change detection, historical data retention, and efficient processing of large data sets.

Establish standards for data naming, definitions, structure, documentation, ownership, lineage, and appropriate use across enterprise reporting.

Support data governance initiatives that create consistent definitions and trusted sources for customers, employees, shipments, financial information, operational metrics, and other key business entities.

Help establish consistent enterprise KPIs and reporting definitions to reduce conflicting calculations and different versions of the same business metric.

Document data sources, pipelines, transformations, dependencies, business rules, data models, and reporting structures.

Maintain visibility into dependencies between source systems, data pipelines, transformations, reporting datasets, and downstream applications.

Participate in the evaluation and implementation of new data technologies, tools, integrations, and architectural improvements.

Work with application developers, infrastructure teams, data analysts, project managers, and business stakeholders to support new projects and data requirements.

Follow appropriate security, access control, data privacy, change management, testing, and development practices when working with enterprise data.

Proactively identify opportunities to improve data reliability, processing performance, automation, scalability, maintainability, and overall data architecture.

Bachelor’s degree in Computer Science, Software Engineering, or a related field; or equivalent practical experience