Sr. Systems Engineer

About the opportunity

Description SAIC is searching for a motivated, career and customer-oriented Sr. AWS Data Engineer who will lead the next phase of our healthcare data platform modernization. This role is central to our evolution from an MSSQL XML object store toward a scalable, cloud-native AWS data architecture — one that enables business stakeholders and analysts to run performant, SQL-based reports and queries against our healthcare data seamlessly. This person will help evaluate and decide the right AWS data strategy for our platform. This is a 100% Remote role. Job Description: Evaluate and recommend the optimal AWS-native data storage and query architecture for our XML object store data — assessing options such as S3 + Athena, Aurora, DynamoDB, Redshift, and OpenSearch based on query patterns, reporting needs, cost, and scalability Design and build the reporting and query layer that allows business stakeholders and non-technical users to run relational SQL queries against healthcare data using familiar tooling Architect the migration path for XML object store data from MSSQL into the target AWS platform, defining storage formats, partitioning strategies, and data organization for optimal query performance Build and maintain AWS data catalog, schemas, and metadata management so that object store data is discoverable and queryable by business users Optimize query performance and cost across chosen AWS services — partitioning, compression, file formats, and query pattern tuning Work directly with business stakeholders and analysts to understand reporting requirements and translate them into durable, performant data models and query patterns Collaborate with backend C#/.NET engineers to ensure data flows cleanly from EDI processing pipelines into the new data layer Implement and maintain CI/CD pipelines for data infrastructure using AWS-native tooling (CodePipeline, CodeBuild, CodeDeploy) Apply infrastructure as code (IaC) practices using AWS CDK, CloudFormation, or Terraform Document architecture decisions, data flows, and data dictionaries clearly for both technical and non-technical audiences Qualifications Education Bachelor's or master's degree in computer science, Engineering, or a related technical discipline required; equivalent practical experience considered Experience Minimum 8 years of experience in software or data engineering with a strong AWS focus Proven experience architecting and executing cloud data platform migrations in production enterprise or healthcare environments Track record of evaluating and selecting AWS data services to meet business reporting and query requirements Experience delivering reporting or analytics solutions that serve non-technical business users Requirements Core Technical Deep hands-on AWS experience across data-oriented services — S3, Athena, Glue, Aurora, DynamoDB, Redshift, OpenSearch, Lambda, IAM, CloudWatch Strong SQL skills — ability to design relational query layers over semi-structured or non-relational data (XML, JSON) Experience working with XML-heavy data stores — parsing, querying, and transforming XML at scale Ability to evaluate trade-offs across AWS data services and make architecture recommendations based on cost, performance, and business requirements Familiarity with AWS analytics and reporting services — Athena, QuickSight, Redshift, or equivalent BI tooling Proficient with Git and GitHub — branching strategies, pull requests, collaborative workflows Familiarity with CI/CD practices and AWS-native tooling (CodePipeline, CodeBuild, CodeDeploy) Infrastructure as code experience (AWS CDK, CloudFormation, or Terraform) Process & Soft Skills Strong ability to communicate technical architecture decisions and trade-offs to non-technical stakeholders Experience gathering and translating business reporting requirements into technical data models Comfortable driving ambiguous architecture decisions to resolution with limited direction Experience with agile methodologies (Scrum, Kanban) and JIRA Strong documentation habits — architecture diagrams, data dictionaries, migration runbooks Nice to Have Experience with healthcare data formats — X12 EDI (837, 835, 277CA), HL7, FHIR Familiarity with C#/.NET backend services for integration touchpoints Experience with Entity Framework migration or deprecation projects Knowledge of HIPAA compliance requirements in cloud data architecture Experience with healthcare payer/PBM systems, clearinghouses, or pharmacy operations AWS certification is a bonus Clearance Requirement: US Citizenship required with the ability to obtain and maintain a Public Trust clearance

Qualifications

• and translate them into durable, performant data models and query patterns Collaborate with backend C#/.
• NET engineers to ensure data flows cleanly from EDI processing pipelines into the new data layer Implement and maintain CI/CD pipelines for data infrastructure using AWS-native tooling (CodePipeline, CodeBuild, CodeDeploy) Apply infrastructure as code (IaC) practices using AWS CDK, CloudFormation, or Terraform Document architecture decisions, data flows, and data dictionaries clearly for both technical and non-technical audiences
• Education Bachelor's or master's degree in computer science, Engineering, or a related technical discipline required; equivalent practical experience considered Experience Minimum 8 years of experience in software or data engineering with a strong AWS focus Proven experience architecting and executing cloud data platform migrations in production enterprise or healthcare environments Track record of evaluating and selecting AWS data services to meet business reporting and query
• Experience delivering reporting or analytics solutions that serve non-technical business users
• Core Technical Deep hands-on AWS experience across data-oriented services — S3, Athena, Glue, Aurora, DynamoDB, Redshift, OpenSearch, Lambda, IAM, CloudWatch Strong SQL skills — ability to design relational query layers over semi-structured or non-relational data (XML, JSON) Experience working with XML-heavy data stores — parsing, querying, and transforming XML at scale Ability to evaluate trade-offs across AWS data services and make architecture recommendations based on cost, performance, and business