AWS Cloud Engineer

Interview process: Onsite (Plano, TX)

We are looking for a highly skilled
Senior AWS Data/Backend Engineer
with strong expertise in
C#, AWS Lambda, AWS Glue
, and distributed caching technologies. The ideal candidate will excel at building and optimizing
high-performance cloud-native APIs
and backend services in a fully AWS-based environment. This role focuses heavily on API scalability, performance tuning, and data pipeline optimization.

Key Responsibilities

• Design, develop, and optimize
  AWS Lambda functions in C#
  for low-latency, high-throughput workloads.
• Implement and manage
  distributed caching
  using Redis/ElastiCache or OpenSearch.
• Enhance and support
  AWS Glue ETL pipelines
  , data structures, and workflows.
• Architect scalable backend services using
  API Gateway, Lambda, S3, and Glue Catalog
  .
• Optimize data querying patterns across
  Aurora, DynamoDB, Redshift
  , or similar databases.
• Perform end-to-end
  performance profiling and bottleneck analysis
  across APIs and data pipelines.
• Improve observability with
  CloudWatch, X-Ray
  , and structured logging.
• Ensure all cloud solutions meet best practices for
  security, scalability, reliability, and cost efficiency
  .
• Collaborate with cross-functional teams to deliver high-performance APIs and backend systems.

Required Skills & Experience

• 5+ years in backend engineering, cloud engineering, or data engineering.
• Strong expertise in
  C#/.NET
  with hands-on AWS Lambda experience.
• Experience implementing
  Redis/ElastiCache or OpenSearch caching layers
  .
• Hands-on with
  AWS Glue, Glue Catalog, ETL optimization, and data lakes
  .
• Strong knowledge of core AWS services:
  Lambda, API Gateway, S3, IAM, CloudWatch
  .
• Experience with cloud databases:
  Aurora, DynamoDB, Redshift
  .
• Strong understanding of
  data modeling, partitioning, and schema optimization
  .
• Excellent debugging, performance tuning, and problem-solving abilities.

Preferred Qualifications

• Experience with
  event-driven architectures
  (Kinesis, Kafka, SNS, SQS).
• Familiarity with
  CI/CD pipelines and automated deployments
  .
• Knowledge of
  AWS cost optimization
  practices.
• Understanding of
  DevOps/SRE monitoring and high-availability concepts
  .