Lead the modernization of a healthcare data platform from an MSSQL XML object store to a scalable AWS architecture. Evaluate AWS storage and query services, design SQL reporting layers, architect data migration and metadata strategies, optimize performance and cost, and build CI/CD and infrastructure-as-code pipelines. Partner with business stakeholders, analysts, and C#/.NET engineers to deliver accessible data models and reliable integrations. Document architecture, data flows, and migration processes while supporting healthcare data and compliance requirements.
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
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
About UsSAIC® is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.
Similar Jobs
Artificial Intelligence • Cloud • Information Technology • Security • Social Impact • Software
Lead the evaluation, training, fine-tuning, deployment, and continuous improvement of AI and machine learning models. Build prompt engineering, model evaluation, benchmarking, and performance-tracking tools; optimize Elasticsearch-backed AI data systems; assess commercial and open-source LLMs; and collaborate with product, engineering, and security teams to deliver safe, scalable AI features.
Top Skills:
A/B TestingAmazon BedrockAmazon SagemakerAnthropicData PipelinesElasticsearchHugging FaceLarge Language ModelsMachine LearningMeta LlmsMistralOpenaiPrompt EngineeringPythonPyTorchScikit-LearnSupervised LearningTensorFlow
Artificial Intelligence • Cloud • Software • Infrastructure as a Service (IaaS)
Design and maintain automated testing frameworks for cloud-scale distributed systems. Build performance, load, stress, integration, API, end-to-end, chaos, security, and infrastructure tests. Integrate continuous testing into CI/CD pipelines, analyze observability data, validate Kubernetes and microservices environments, and collaborate with Engineering and SRE teams to improve reliability. The role also participates in on-call rotations and helps establish QA strategy and standards across GPU infrastructure, serverless endpoints, storage, billing, and event-driven systems.
Top Skills:
AWSAzureChaos MeshCi/CdDatadogGCPGoGrafanaGraphQLGremlinInfrastructure As Code (Iac)JmeterK6KafkaKubernetesLitmuschaosLocustOpentelemetryPrometheusPythonRabbitMQRedisTypescript
Artificial Intelligence • Cloud • Software • Infrastructure as a Service (IaaS)
Provide first-line technical and non-technical support through email, phone, chat, and video. Manage and resolve L1 tickets, troubleshoot system behavior and configurations, document solutions, explain technical issues clearly, and escalate complex problems to L2 or engineering teams. The role requires shell scripting, Python, SQL, REST APIs, GraphQL, and customer support experience, with possible weekend and allocated-shift availability.
Top Skills:
Crm/Ticketing ToolsDockerGoogle MeetGraphQLLinuxObservability ToolsPythonRest ApisShell ScriptingSQLSshTerminal CommandsZendeskZoom
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
