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Role Summary:
We are looking for an AWS Connect Engineer who can both design and operate the Amazon Connect contact center and build the reporting and analytics that leadership relies on. The ideal candidate is equally comfortable building IVR/contact flows and AI-assisted quality evaluation as they are writing SQL against the analytics data lake and standing up automated daily reports. You will own the Connect platform end-to-end - configuration, routing, integrations, quality, and metrics - for a multi-tower service desk operating across queues such as TSD-L1, TSD-L2, Clinical Service Desk, and Enhanced/C-Suite support.
What makes this role different This is not a config-only role. You will also produce the numbers leadership acts on - calls offered/answered, ASA, AHT, service levels, and a defensible true-abandonment figure - using Connect metrics, the analytics data lake, and automated reporting. Strong SQL and AWS reporting skills are as important as Connect configuration. |
Key Responsibilities
A. Amazon Connect - Design & Configuration
Contact flows & IVR: design, build, and maintain inbound flows, IVR menus, prompts (S3 / TTS / SSML), hours of operation, holidays, and error handling
Routing: configure queues, routing profiles, quick connects, and multi-queue fallback/overflow logic (e.g., mutual fallback between towers)
Agent experience: manage security profiles, users, agent hierarchies, and the Contact Control Panel / agent workspace
Data Tables & dynamic config: use Amazon Connect Data Tables for no-code operational changes such as outage announcements, holiday flags, and dynamic prompts
Telephony: claim and manage DIDs / toll-free numbers coordinate carrier and number porting where required
B. Quality, AI & Contact Lens
Contact Lens: enable and configure conversational analytics (post-call), category rules, sentiment, and redaction
Evaluation forms: build and maintain agent evaluation forms, including generative-AI (automated) scoring and rule-based automation
QA operations: support calibration between AI and human reviewers tune evaluation logic and thresholds
C. Integrations
ITSM: integrate Connect with ServiceNow (screen-pop, ticket create/update, resolver-group routing)
Identity & collaboration: work with Active Directory / Entra ID and Microsoft Teams as applicable
Serverless glue: build and maintain AWS Lambda functions used within flows and for automation
D. Reporting, Metrics & Analytics (equal priority)
Built-in reporting: create, schedule, and maintain historical & real-time metrics reports configure S3 export and scheduled delivery
Metrics APIs: use GetMetricDataV2 to programmatically pull queue/agent metrics (service level thresholds, ASA, AHT, abandonment) at custom intervals and time zones
Analytics Data Lake / Athena: enable the Connect analytics data lake write Athena (Presto/Trino) SQL against contact_record / contact_statistic_record for contact-level accuracy - including true-abandonment logic using Agent Connection Attempts
Automated distribution: build serverless pipelines (EventBridge → Lambda → SES / SNS) to compute KPIs and email daily/weekly reports land data in S3
BI dashboards: prepare data for and support Amazon QuickSight and/or Power BI dashboards ensure clean, model-ready datasets
Metric integrity: understand nuanced Connect metric behavior (e.g., contacts handled vs. queued, agent non-response vs. customer abandon) and produce numbers that reconcile and are defensible to leadership
E. Operations & Governance
Stabilization & go-live: support go-live ramp-up, monitoring, and post-go-live stabilization
Change management: follow least-privilege and change-control practices document configurations and runbooks
Stakeholder support: translate business/operational needs into Connect configuration and reporting present results clearly to PMO and C-level stakeholders
Required Skills & Experience
Amazon Connect (must-have)
2+ years hands-on building Amazon Connect contact flows, routing profiles, queues, and IVR
Contact Lens, evaluation forms, and quality-management configuration
Amazon Connect Data Tables, prompts (SSML/TTS), hours of operation, and quick connects
Experience with queue fallback/overflow and multi-tower routing designs
AWS platform & reporting (must-have)
Strong SQL - able to write and optimize analytical queries (Athena / Presto-Trino preferred)
AWS Lambda (Python or Node.js), IAM (least-privilege policies), Amazon S3
Amazon Connect metrics: GetMetricDataV2 / historical & real-time reports metric definitions
Amazon EventBridge (scheduling) and Amazon SES/SNS for automated report delivery
Amazon Connect analytics data lake / AWS Glue / Lake Formation exposure
BI tooling - Amazon QuickSight and/or Microsoft Power BI
Comfortable in advanced Excel for data validation and ad-hoc analysis
Integrations & tooling (strong plus)
ServiceNow integration with Connect (CTI, screen-pop, incident automation)
AWS CLI / CloudFormation or Terraform for repeatable deployments
Amazon Lex (chatbot) and Kinesis (CTR streaming) exposure
Active Directory / Entra ID, Microsoft Teams
Soft skills
Clear communicator who can explain metrics and trade-offs to non-technical leadership
Detail-oriented and accuracy-driven validates numbers before they are reported
Comfortable working across locations and time zones with PMO governance
Preferred Qualifications
Certifications: AWS Certified Cloud Practitioner or Solutions Architect - Associate any Amazon Connect specialty training
Domain: prior work in IT Service Desk / ITIL environments or healthcare contact centers
Education: Bachelor's in Computer Science, IT, or equivalent practical experience
What Success Looks Like (First 90 Days)
Owns and documents the existing Connect configuration (flows, queues, routing, evaluation forms)
Delivers a reliable daily/weekly KPI report (offered, answered, ASA, AHT, true-abandon %) that reconciles and is trusted by leadership
Stands up or stabilizes the automated reporting pipeline (data lake / Lambda / scheduled delivery)
Implements at least one operational improvement (e.g., outage-announcement via Data Tables, routing optimization, or AI evaluation tuning)
How to evaluate candidates (for the hiring panel) . Ask them to whiteboard a contact flow with multi-queue fallback and an outage announcement. . Give a SQL scenario: compute true abandonment (customer disconnected in queue, no agent connected) from contact records. . Probe metric nuance: why can contacts handled exceed contacts queued, and how they'd report a defensible abandon rate. . Ask how they'd schedule and email a daily report without manual effort (EventBridge → Lambda → SES). |
Job ID: 153905119
Skills:
Typescript, Mockito, JUnit, Javascript, Spring Boot, Rest Api, Sql, Microservices
Skills:
.Net Core, .NET 6, Functions, Asp.net Mvc, SQL Server, ASP.NET, Restful Apis, complex queries, stored procedures
Skills:
snowflake , Unix, Machine Learning, Sql, Python Programming, Tensorflow, MLops, Pytorch, Linux, MySQL, Flask, FastAPI, LangChain, LLMs, AI Agents, Scikit-Learn, AutoGen, Multi-Agent Systems, Model Deployment, RAG, Prompt Engineering
Skills:
Java, Hibernate, Tomcat, Design Patterns, Spring Boot, Jsp, J2EE, Sql, Angular, Jms, Core Java, Owasp, Pci, Reactjs, Javaee, Struts, Spring Framework, Ejb, Servlets, Design Principles, SOAP Web-services, RESTful web-services, Micro-services
Skills:
Java, C, Sql, Nosql, Javascript, Restful Apis, Python, GraphQL services, GenAI Application development, Llm, GitHub Copilot, AI-assisted software development tools, Agent SDKs