The Role
Build and maintain .NET AWS Lambda services, shared client libraries, Kafka producers and backfill tooling. Design data pipelines with DynamoDB and SQS, implement AVRO schemas and Schema Registry, integrate third-party REST APIs, ensure robust testing and observability using CloudWatch and Lambda Insights.
Summary Generated by Built In
Dev / Senior Developer
The Dev / Senior Developer is the primary builder for both Lambda services, the shared client library, Kafka producer logic, and backfill tooling. This role requires strong backend engineering skills with hands-on AWS serverless experience.
Required Skills:
- .NET: 4+ years production experience in the primary Lambda runtime; ability to write clean, testable, well-structured code with proper error handling and logging using AWS Lambda's .NET managed runtime (Amazon.Lambda.Core).
- AWS Lambda & serverless: Practical experience building and deploying Lambda functions, including timeout management, concurrency configuration (reserved and provisioned), cold-start optimization, and Step Functions for orchestration; familiarity with Lambda deployment via AWS SAM or CDK and monitoring via CloudWatch Logs and Lambda Insights.
- REST API integration: Experience consuming third-party REST APIs with pagination, rate-limit handling, retry/back off strategies, and authentication (API key headers); ability to store and rotate API credentials securely using AWS Secrets Manager or Parameter Store. Familiarity with marketing platform APIs is a plus.
- Apache Kafka: Hands-on experience producing messages to Kafka topics on Amazon MSK, including AVRO serialization, Schema Registry integration, producer configuration (acks, retries, idempotency), and troubleshooting publish failures.
- AVRO & Schema Registry: Ability to define, version, and register AVRO schemas; understanding of schema evolution (backward/forward compatibility) and contract-first design.
- Amazon DynamoDB: Experience designing table schemas (partition/sort keys), managing read/write capacity, implementing TTL policies, and using DynamoDB for cursor/state persistence and configuration storage; familiarity with DynamoDB conditional writes for idempotent operations.
- Data pipeline design: Understanding of batch/incremental ingestion patterns, idempotency strategies (composite keys, deduplication), cursor-based change tracking, and data correctness in distributed systems; experience using SQS as a buffer between pipeline stages for resilience and flow control.
- Testing: Strong unit testing discipline; experience with integration testing using mocks, stubs, or sandbox environments for external APIs and Kafka; familiarity with running integration tests against local AWS service emulators (LocalStack) or AWS sandbox accounts.
Desirable:
- Experience with Snowflake or data warehouse ingestion patterns.
- Familiarity with API v2 (contacts, lists, list changes endpoints).
- Experience with historical backfill tooling (phased execution, rate-limit-aware replay).
- Knowledge of PII handling and data minimization in event-driven architectures, including AWS KMS encryption and CloudWatch log filtering for sensitive fields
Skills Required
- .NET: 4+ years production experience with AWS Lambda's .NET managed runtime (Amazon.Lambda.Core), writing clean, testable code with proper error handling and logging
- AWS Lambda & serverless: building/deploying Lambdas, timeout and concurrency management, cold-start optimization, Step Functions, deployment via AWS SAM or CDK, CloudWatch Logs and Lambda Insights monitoring
- REST API integration: consuming third-party REST APIs with pagination, rate-limit handling, retry/backoff strategies, authentication, and secure credential storage/rotation using AWS Secrets Manager or Parameter Store
- Apache Kafka: producing messages to Kafka (Amazon MSK) with AVRO serialization, Schema Registry integration, and producer configuration (acks, retries, idempotency)
- AVRO & Schema Registry: define, version, register AVRO schemas and manage schema evolution and contract-first design
- Amazon DynamoDB: design table schemas (partition/sort keys), manage capacity and TTL, use DynamoDB for cursor/state persistence, and conditional writes for idempotency
- Data pipeline design: batch/incremental ingestion patterns, idempotency strategies, cursor-based change tracking, and using SQS as a buffer between pipeline stages
- Testing: strong unit testing discipline and integration testing using mocks/stubs or sandbox environments; familiarity with LocalStack or AWS sandbox accounts
- Experience with Snowflake or data warehouse ingestion patterns
- Familiarity with API v2 (contacts, lists, list changes endpoints)
- Experience with historical backfill tooling (phased execution, rate-limit-aware replay)
- Knowledge of PII handling and data minimization in event-driven architectures, including AWS KMS encryption and CloudWatch log filtering for sensitive fields
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Genzeon advances highly effective, secure, and innovative technology solutions for healthcare and retail clients, including intelligent automation, security, compliance, and cloud services. Founded in 2009, by a group of leaders with a shared commitment to unleashing human potential, Genzeon is blazing new trails in fueling innovation, transforming businesses and unleashing efficiency. Our vision is to Dream Big, Deliver Excellence
