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 ResponsibilitiesData 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, or similar technologies.
- Strong understanding of dimensional modeling, star/snowflake schemas, and data warehousing concepts.
- Experience with AWS cloud services and data analytics architecture.
- Proficiency in Python and/or other scripting languages.
- Experience with Git and CI/CD deployment practices.
Preferred Qualifications- AWS Certifications (e.g., AWS Certified Data Engineer, AWS Certified Solutions Architect, AWS Certified Data Analytics).
- Experience with Redshift, Athena, and large-scale cloud data platforms.
- Knowledge of data governance, data quality frameworks, and metadata management.
- Experience working in Agile/Scrum environments.
- Familiarity with healthcare, federal, financial, or regulated industry reporting environments.
Technical SkillsRequired- AWS QuickSight
- SQL
- Python
- AWS Glue
- Amazon Redshift
- Amazon S3
- Amazon Athena
- ETL/ELT Development
- Data Modeling
- Data Warehousing
Preferred- Apache Spark
- Lambda
- Airflow
- Terraform
- Tableau or Power BI
- Snowflake
Key Competencies- Strong analytical and problem-solving skills.
- Excellent communication and stakeholder engagement abilities.
- Ability to translate business requirements into technical solutions.
- Attention to detail and commitment to data quality.
- Strong collaboration and teamwork skills.
Nice-to-Have Experience- Federal government or healthcare data environments.
- Building executive dashboards and KPI scorecards.
- Data migration and modernization initiatives.
- Real-time or near-real-time analytics solutions.
Target Experience Level: Junior-Mid (5-10+ years)
Primary Focus: Data Engineering, AWS Data Platform, BI Reporting, AWS Quick Sight Dashboard Development.
