BI Reporting & AWS Quick Sight
Tria Federal
| Company | Tria Federal |
| Category | Data & Analytics |
| Location | Remote (United States) |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 29 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Who we are:
Tria Federal delivers digital services and technology solutions that support the health and safety of veterans, service members and civilians. For two decades, federal agencies have relied on Tria companies to advance their critical missions and modernize their systems, so that they can uphold their commitment to the American people. Today, we are pushing the boundaries of possibility through partnerships and investments in artificial intelligence and emerging technologies, developing solutions for the biggest challenges that government will face tomorrow.
We are proud to employ and support military veterans who bring mission-first mindset, technical expertise, and leadership qualities that strengthen our work. Veterans, transitioning service members, and military spouses are strongly encouraged to apply.
Job Description: We are seeking a highly skilled Data Engineer with strong Business Intelligence (BI) reporting experience to design, build, and maintain scalable data solutions that support enterprise analytics and reporting needs. The ideal candidate will have expertise in data engineering, data warehousing, ETL/ELT development, and dashboard creation using AWS Quick Sight . This role will collaborate closely with business stakeholders, analysts, and technical teams to transform data into actionable insights.
Key Responsibilities
Data Engineering
Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
Build and optimize data models, data lakes, and data warehouses in AWS environments.
Integrate data from multiple internal and external sources while ensuring data quality and consistency.
Implement data governance, validation, monitoring, and security best practices.
Optimize database performance, query execution, and data processing workflows.
BI Reporting & Analytics
Develop, maintain, and enhance interactive dashboards and reports using AWS QuickSight .
Translate business requirements into meaningful KPIs, metrics, and visualizations.
Design data models and datasets optimized for reporting and analytics.
Collaborate with business users to gather reporting requirements and provide actionable insights.
Create self-service reporting solutions for business stakeholders.
Ability to configure and manage Row-Level Security (RLS) and apply it across datasets, analyses, and dashboards.
Ability to securely embed QuickSight dashboards into web portals/applications with integrated application-level security and RLS-based access control.
Ability to create and manage QuickSight Topics and Spaces to enable natural language querying and self-service analytics for business users.
Ability to provide AI-powered insights and dashboard interactions through Amazon QuickSight Q/Generative BI capabilities.
Develop cloud-native data solutions leveraging AWS services.
Work with AWS services such as:
Amazon S3
AWS Glue
Amazon Redshift
Amazon Athena
AWS Lambda
Amazon RDS
AWS Quick Sight
Implement data security, access controls, and compliance requirements within AWS.
Collaboration & Support
Partner with business analysts, data scientists, and application teams to deliver analytics solutions.
Provide technical guidance on reporting architecture and dashboard best practices.
Troubleshoot data issues and support production reporting environments.
Document data pipelines, reporting solutions, and technical processes.
Required Qualifications
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field.
5+ years of experience in Data Engineering, Data Warehousing, or BI Development.
Hands-on experience building and maintaining dashboards using AWS QuickSight .
Strong experience with SQL and relational databases.
Experience developing ETL/ELT pipelines using AWS Glue, Python, Spark,
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