Data Engineer - SQL

R+L Carriers • Ocala, FL

3d • Onsite

About The Position

The Data Engineer develops and maintains data pipelines that move information from operational business systems into the company’s enterprise data platform and data lake. The role designs ETL and ELT processes with Azure Data Factory and related Azure technologies, supports the Azure Data Lake environment, and builds integrations from enterprise applications, APIs, databases, and files. It also develops SQL assets and curated datasets for Power BI and other analytics tools, while maintaining data models for reporting, analytics, historical analysis, and KPI measurement.

The position focuses on data reliability, quality, governance, performance, and accessibility. The Data Engineer establishes validation and monitoring processes, supports consistent enterprise definitions and trusted data sources, documents pipelines and data dependencies, and identifies opportunities to improve data architecture. The role collaborates with developers, infrastructure teams, analysts, project managers, and business stakeholders to meet data and reporting needs, following appropriate security, privacy, testing, and change-management practices.

This position is onsite in Ocala, Florida. Applicants must be U.S. citizens or permanent residents of the United States. A bachelor’s degree in Computer Science, Software Engineering, or a related field is required, or equivalent practical experience. Three or more years of relevant experience is required. Python experience is required.

Requirements

• At least 3 years of experience in data engineering, data integration, database development, business intelligence engineering, or a related technical role.
• Strong experience with Microsoft Azure data technologies, particularly Azure Data Factory, Azure Data Lake Storage, and Databricks.
• Strong SQL skills, including complex queries, views, stored procedures, transformations, and reporting datasets.
• Experience designing, developing, and maintaining ETL and ELT pipelines integrating multiple enterprise data sources.
• Experience integrating data through REST APIs, databases, file transfers, JSON, CSV, flat files, and other common methods.
• Strong understanding of relational databases, data structures, database relationships, data types, indexing, and query optimization.
• Understanding of data warehousing, dimensional modeling, fact and dimension tables, star schemas, and analytics-oriented data structures.
• Experience preparing and modeling data for Power BI or similar business intelligence and visualization platforms.
• Understanding of Power BI data requirements, semantic models, relationships, refresh processes, and reporting performance.
• Experience troubleshooting and optimizing pipelines, SQL queries, transformations, and large data-processing workloads.
• Knowledge of incremental loading, change data capture concepts, data synchronization, data dependencies, and historical data management.
• Experience implementing data validation, reconciliation, monitoring, logging, error handling, and data quality processes.
• Understanding of data governance, including ownership, business definitions, lineage, documentation, access controls, quality, and trusted sources.
• Ability to understand business processes and translate reporting requirements into scalable technical data solutions.
• Ability to analyze data discrepancies and identify whether the cause is in source systems, integrations, transformations, data models, or reporting layers.
• Experience with Python for data processing, automation, integration, or data engineering.
• Familiarity with Git or other source control and development lifecycle practices.
• Familiarity with Azure security, role-based access control, service accounts, credentials, and secure data integration.
• Strong analytical, troubleshooting, communication, organization, documentation, and problem-solving skills.
• Ability to explain technical data concepts, issues, dependencies, and recommendations to technical and non-technical stakeholders.
• Ability to work independently and collaborate across application development, infrastructure, analytics, project management, and business teams.
• Ability to take ownership of critical data processes and proactively identify potential failures, performance issues, data quality concerns, and architectural improvements.
• Ability to manage multiple priorities in a fast-paced environment with changing business and reporting needs.
• Ability to read, write, and speak English fluently.
• Must be a U.S. citizen or permanent resident of the United States.
• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

Nice To Haves

• Experience working with data from ERP, CRM, transportation, logistics, financial, warehouse, customer service, or other enterprise business systems.

Responsibilities

• Develop, maintain, monitor, and optimize pipelines that move data from operational business systems into the 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 Azure Data Lake environment, including organization, storage structures, workflows, access, and reliability.
• Architect integrations and data feeds from enterprise applications, APIs, databases, files, and other internal and external sources.
• Build ingestion processes for structured and semi-structured data, including SQL data, APIs, JSON, CSV, and flat files.
• Troubleshoot feed failures, pipeline errors, processing issues, data discrepancies, and other problems affecting data availability or accuracy.
• Monitor and improve pipeline and query performance, processing times, resource utilization, and platform efficiency.
• Develop and maintain SQL queries, views, stored procedures, transformations, and reusable data structures for reporting and business applications.
• Create curated datasets and reporting views for Power BI and other analytics tools.
• Work with Power BI developers and data analysts to translate reporting needs into appropriate data structures and models.
• Design and maintain data models for enterprise reporting, analytics, operational reporting, historical analysis, and KPI measurement.
• Apply dimensional modeling principles where appropriate, including fact and dimension tables, relationships, measures, historical data, and common business entities.
• Identify ways to make business data easier to access, understand, analyze, and use for decision-making.
• Establish data quality controls, validation, reconciliation, and monitoring to identify missing, inaccurate, duplicated, or inconsistent data.
• Develop incremental loading, change detection, historical retention, and large-data processing processes.
• Establish data naming, definition, structure, documentation, ownership, lineage, and appropriate-use standards.
• Support data governance initiatives and trusted, consistent definitions for key business entities and information.
• Help establish consistent enterprise KPIs and reporting definitions.
• Document data sources, pipelines, transformations, dependencies, business rules, models, and reporting structures.
• Maintain visibility into dependencies among source systems, pipelines, transformations, reporting datasets, and downstream applications.
• Evaluate and implement data technologies, tools, integrations, and architectural improvements.
• Collaborate with application developers, infrastructure teams, analysts, project managers, and business stakeholders on projects and data requirements.
• Follow security, access control, privacy, change-management, testing, and development practices when working with enterprise data.
• Proactively identify improvements to data reliability, performance, automation, scalability, maintainability, and architecture.

Benefits

• Medical, dental, and vision insurance.
• 401(k) retirement plan with company matching contributions.
• Paid vacation and holidays.
• Vacation lodging at employee resorts in Daytona Beach, Florida; Big Bear Lake, California; Pigeon Forge, Tennessee; and Ocean Isle Beach, North Carolina.
• Excellent compensation and a comprehensive benefits package.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level