Sr. Systems Engineer (AWS Data Engineer)

SAIC•El Paso, TX

9d•Remote

About The Position

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.

Requirements

AWS data strategy
AWS data storage and query architecture
S3 + Athena
Aurora
DynamoDB
Redshift
OpenSearch
SQL
XML object store data
MSSQL
AWS data catalog
schemas
metadata management
query performance
cost optimization
partitioning
compression
file formats
query pattern tuning
data models
EDI processing pipelines
CI/CD pipelines
AWS-native tooling
CodePipeline
CodeBuild
CodeDeploy
infrastructure as code (IaC)
AWS CDK
CloudFormation
Terraform
architecture decisions
data flows
data dictionaries

Nice To Haves

C#/.NET engineers

Responsibilities

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