Data Engineer & Developer

## Description

**Overall Responsibility:**

The Data Engineer & Developer is responsible for designing, developing, testing, and maintaining SQL-based data solutions that support operational processing, analytics, and enterprise reporting. This role focuses on hands-on development within SQL Server and Microsoft Fabric database workloads, including the creation of T-SQL stored procedures, views, functions, scripts, and scheduled jobs that enable reliable data movement, transformation, and downstream consumption. The position also supports the organization’s transition toward Microsoft Fabric by applying modern ELT patterns, environment-aware deployment practices, version control discipline, and repeatable release methods. This role is development-focused and does not include database administration responsibilities such as backups, patching, high availability/disaster recovery, or server administration.

**This role is to be hired in San Pedro Sula, Honduras.**

**Duties:**

**SQL Development & Data Solutions Engineering**

• Design, develop, test, and maintain T-SQL stored procedures, functions, views, scripts, and complex queries supporting operational and analytical workloads.
• Build and apply robust SQL development patterns, including parameterization, transaction handling, idempotency, exception handling, and logging/auditing.
• Develop transformation logic supporting incremental loads, late-arriving data, reprocessing, and traceability across environments.

**Performance Optimization & Code Quality**

• Refactor and optimize SQL code by analyzing execution plans, improving query performance, and implementing effective indexing strategies.
• Support data quality and reconciliation by embedding validation checkpoints, monitoring, and exception handling into solutions.
• Contribute to development standards such as naming conventions, SQL style guidelines, and code review practices.

**Data Pipelines, Ingestion & Architecture**

• Implement ingestion and ELT patterns using layered architectures (landing, staging, curated) for reliable data processing.
• Support ingestion from SQL Server, cloud/on-prem systems, and APIs using standardized methods.
• Create and manage SQL-based objects within Microsoft Fabric (Warehouse, Lakehouse SQL endpoints, and related artifacts).

**Automation, Scheduling & DevOps Practices**

• Develop and maintain SQL Server Agent jobs, schedules, alerts, and automation workflows.
• Implement job orchestration patterns that improve reliability, handle failures, and reduce manual dependencies.
• Use GitHub for version control and participate in CI/CD processes to ensure safe and repeatable deployments.

**Collaboration, Governance & Documentation**

• Collaborate with Data Engineering and platform teams to align with architecture standards, governance, and release processes.
• Document database objects, dependencies, deployment procedures, and operational runbooks for maintainability and auditability.
• Perform additional duties and special projects aligned with enterprise data engineering and analytics priorities.

## Qualifications
**Education and Experience:**

• Bachelor's degree in computer science, Information Systems, Information Technology, Software Engineering, Data Engineering, or a related field; equivalent relevant experience may be considered.
• Minimum of 4 or more years of hands-on SQL Server development experience with strong proficiency in T-SQL and SQL-based application or data workload support.
• Demonstrated experience building and maintaining stored procedures, user-defined functions, views, complex queries, and performance-conscious SQL solutions in a professional environment.
• Hands-on experience creating, scheduling, monitoring, and troubleshooting SQL Server Agent jobs and related automation workflows.
• Practical experience using GitHub or a comparable version control platform for branching, pull requests, code reviews, and controlled release practices.
• Exposure to CI/CD concepts and deployment discipline as applied to database changes, SQL artifacts, and/or data pipeline assets.
• Demonstrated experience working with Microsoft Fabric database workloads such as Fabric Warehouse and/or Lakehouse SQL endpoints.
• Working knowledge of Fabric architecture concepts relevant to development, including environment separation, workspace and capacity alignment, and OneLake organizational principles.
• Experience implementing ingestion and ELT patterns, including layered data processing, incremental loads, repeatable transformations, and dependency-aware workflow design.
• Experience with API ingestion patterns, JSON parsing, data quality checks, reconciliation techniques, or downstream analytics consumption considerations is preferred.
• **Bilingual (Spanish/English) required**

**Skills:**

• Advanced SQL and T-SQL development skills, including query design, stored procedure development, troubleshooting, and performance optimization.
• Strong understanding of SQL development best practices such as transaction control, error handling, idempotency, logging, parameterization, and modular design.
• Knowledge of job scheduling, workload automation, notification handling, and dependency-aware orchestration using SQL Server Agent or equivalent scheduling tools.
• Working knowledge of Microsoft Fabric database development concepts, including SQL-based warehousing, Lakehouse SQL querying, and environment-aware promotion practices.
• Ability to design and support ELT and ingestion processes using layered architectures, repeatable transformations, and practical data movement controls.
• Strong version control and deployment discipline using GitHub, code reviews, pull requests, and structured release workflows.
• Analytical and problem-solving skills with the ability to diagnose data processing issues, optimize performance, and improve operational reliability.
• Strong documentation habits with the ability to create clear runbooks, standards, deployment notes, and technical support materials.
• Effective communication and collaboration skills, with the ability to work across technical teams, business stakeholders, and platform support groups.
• Commitment to data quality, governance, continuous improvement, and delivery of reliable, maintainable, and scalable data solutions.