So, what’s the role all about?

Data Engineer at NICE CXone sits between the teams that build data products and the infrastructure that runs them. We keep Snowflake environments healthy, get changes deployed safely through maintenance windows, and make sure the pipelines and systems our partners depend on stay observable and reliable. 

Your time will be split between operational work — coordinating and executing change requests, monitoring systems, supporting deployments — and project work focused on improving how we operate: better automation, cleaner alerting, more resilient processes. 

How will you make an impact?  

Release & deployment operations 

• Coordinate and execute build and release activities across multiple production regions within scheduled maintenance windows 
• Manage day-to-day operations of release pipelines, including Jenkins and GitHub Actions workflows, on behalf of data engineering teams 
• Author and manage Change Requests in ServiceNow, following CAB and CHG guidelines 
• Respond to platform alerts, investigate issues, and keep stakeholders informed 

Observability & support 

• Perform ongoing monitoring and maintenance of Snowflake environments — warehouse performance, access, and cost 
• Monitor MSK (Kafka) consumers and producers via CloudWatch; escalate or resolve anomalies 
• Keep runbooks current and contribute to post-incident reviews 
• Support data engineering teams with deployment questions and environment issues 

Improvement & automation 

• Identify and prototype improvements to DataOps processes through scripting and automation 
• Build and maintain tooling that reduces toil and improves the reliability of our release pipeline 

Day-to-Day Tech 

• Snowflake
• AWS (S3, IAM, CloudWatch, Lambda)
• Jenkins  ·  GitHub Actions 
• MSK / Kafka 
• Apache Airflow 
• Python 
• ServiceNow 
• Jira

Have you got what it takes?

• 3+ years in a DataOps, Platform Operations, or DevOps/SRE role supporting data infrastructure 
• Snowflake: hands-on with RBAC, warehouses, multi-environment administration, and SQL 
• AWS: S3, IAM, CloudWatch, Lambda — comfortable in the console and with the CLI 
• Experience defining and working within CI/CD pipelines using Jenkins and/or GitHub Actions 
• Python scripting for operational automation 
• Experience working within a formal change management process: CRs, maintenance windows, approvals 
• Clear communicator when things break — you keep stakeholders informed without being asked 
• Comfortable working async across time zones in a distributed team 
• Familiar with AI tools and comfortable using them in day-to-day work 

Nice to Have 

• Apache Airflow — DAG monitoring and operational support 
• MSK / Kafka operational experience 
• Infrastructure as Code experience — Terraform or similar 
• Prometheus & Grafana for monitoring and dashboards 

What’s in it for you?
Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr!

Enjoy NICE-FLEX! 
At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10730
Reporting into: Manager, Engineering, Data CX
Role Type: Individual Contributor

So, what’s the role all about?

Associate Data Engineer at NICE CXone sits between the teams that build data products and the infrastructure that runs them. We keep Snowflake environments healthy, get changes deployed safely through maintenance windows, and make sure the pipelines and systems our partners depend on stay observable and reliable. 

Your time will be split between operational work — coordinating and executing change requests, monitoring systems, supporting deployments — and project work focused on improving how we operate: better automation, cleaner alerting, more resilient processes. 

How will you make an impact?  

Release & deployment operations 

• Coordinate and execute build and release activities across multiple production regions within scheduled maintenance windows 
• Manage day-to-day operations of release pipelines, including Jenkins and GitHub Actions workflows, on behalf of data engineering teams 
• Author and manage Change Requests in ServiceNow, following CAB and CHG guidelines 
• Respond to platform alerts, investigate issues, and keep stakeholders informed 

Observability & support 

• Perform ongoing monitoring and maintenance of Snowflake environments — warehouse performance, access, and cost 
• Monitor MSK (Kafka) consumers and producers via CloudWatch; escalate or resolve anomalies 
• Keep runbooks current and contribute to post-incident reviews 
• Support data engineering teams with deployment questions and environment issues 

Improvement & automation 

• Identify and prototype improvements to DataOps processes through scripting and automation 
• Build and maintain tooling that reduces toil and improves the reliability of our release pipeline 

Day-to-Day Tech 

• Snowflake
• AWS (S3, IAM, CloudWatch, Lambda)
• Jenkins  ·  GitHub Actions 
• MSK / Kafka 
• Apache Airflow 
• Python 
• ServiceNow 
• Jira

Have you got what it takes?

• 2+ years in a DataOps, Platform Operations, or DevOps/SRE role supporting data infrastructure 
• Snowflake: hands-on with RBAC, warehouses, multi-environment administration, and SQL 
• AWS: S3, IAM, CloudWatch, Lambda — comfortable in the console and with the CLI 
• Experience defining and working within CI/CD pipelines using Jenkins and/or GitHub Actions 
• Python scripting for operational automation 
• Experience working within a formal change management process: CRs, maintenance windows, approvals 
• Clear communicator when things break — you keep stakeholders informed without being asked 
• Comfortable working async across time zones in a distributed team 
• Familiar with AI tools and comfortable using them in day-to-day work 

Nice to Have 

• Apache Airflow — DAG monitoring and operational support 
• MSK / Kafka operational experience 
• Infrastructure as Code experience — Terraform or similar 
• Prometheus & Grafana for monitoring and dashboards 

What’s in it for you?
Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr!

Enjoy NICE-FLEX! 
At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10733
Reporting into: Manager
Role Type: Individual Contributor

So, what’s the role all about?
We are seeking an experienced Manager, Engineering to lead a globally distributed team responsible for optimizing and managing data pipelines, real-time data processing, and database operations. The ideal candidate will have strong technical expertise in SQL, databases, Kafka, Flink, Airflow, and AWS, along with experience in managing remote teams across multiple time zones. 

How will you make an impact?  

• Lead and mentor a distributed DataOps team, ensuring high performance and collaboration across different regions. 
• Oversee the design, development, and maintenance of scalable data pipelines and streaming applications. 
• Manage and optimize database operations, ensuring data integrity, performance, and security. 
• Implement and maintain real-time data processing workflows using Kafka and Flink. 
• Collaborate with engineering, analytics, and business teams to ensure seamless data flow and accessibility. 
• Develop and enforce best practices for data governance, monitoring, and observability. 
• Drive automation and efficiency improvements in DataOps processes. 
• Ensure high availability, reliability, and performance of data infrastructure. 
• Manage project timelines, resource allocation, and stakeholder expectations. 

Have you got what it takes?

• Bachelor's degree in Computer Science, Engineering, or a related field, OR 5+ years of experience in DataOps, Data Engineering, or a related field. 
• Proven experience managing and leading remote teams across multiple time zones. 
• Strong proficiency in SQL and database management (e.g., Snowflake, SQL, NoSQL databases). 
• Expertise in real-time data processing technologies such as Kafka and Flink. 
• Experience with Airflow for workflow orchestration. 
• Experience with cloud-based data platforms, particularly AWS. 
• Familiarity with infrastructure-as-code and automation tools. 

Preferred Qualifications: 

• Experience working in a fast-paced, globally distributed environment. 
• Knowledge of CI/CD pipelines for data workflows. 
• Understanding of data security and compliance best practices. 

This job description is not intended to be all-inclusive, and employees will also perform other reasonable related business duties as assigned by immediate supervisor and other management as required.

This organization reserves the right to revise or change job duties as the need arises. This job description does not constitute a written or implied contract of employment.​

What’s in it for you?
Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr!

Enjoy NICE-FLEX! 
At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10613
Reporting into: Manager, Network Operations
Role Type: Individual Contributor

So, what’s the role all about?

Associate Data Engineer at NICE CXone sits between the teams that build data products and the infrastructure that runs them. We keep Snowflake environments healthy, get changes deployed safely through maintenance windows, and make sure the pipelines and systems our partners depend on stay observable and reliable. 

Your time will be split between operational work — coordinating and executing change requests, monitoring systems, supporting deployments — and project work focused on improving how we operate: better automation, cleaner alerting, more resilient processes. 

How will you make an impact?  

Release & deployment operations 

• Coordinate and execute build and release activities across multiple production regions within scheduled maintenance windows 
• Manage day-to-day operations of release pipelines, including Jenkins and GitHub Actions workflows, on behalf of data engineering teams 
• Author and manage Change Requests in ServiceNow, following CAB and CHG guidelines 
• Respond to platform alerts, investigate issues, and keep stakeholders informed 

Observability & support 

• Perform ongoing monitoring and maintenance of Snowflake environments — warehouse performance, access, and cost 
• Monitor MSK (Kafka) consumers and producers via CloudWatch; escalate or resolve anomalies 
• Keep runbooks current and contribute to post-incident reviews 
• Support data engineering teams with deployment questions and environment issues 

Improvement & automation 

• Identify and prototype improvements to DataOps processes through scripting and automation 
• Build and maintain tooling that reduces toil and improves the reliability of our release pipeline 

Day-to-Day Tech 

• Snowflake
• AWS (S3, IAM, CloudWatch, Lambda)
• Jenkins  ·  GitHub Actions 
• MSK / Kafka 
• Apache Airflow 
• Python 
• ServiceNow 
• Jira

Have you got what it takes?

• 2+ years in a DataOps, Platform Operations, or DevOps/SRE role supporting data infrastructure 
• Snowflake: hands-on with RBAC, warehouses, multi-environment administration, and SQL 
• AWS: S3, IAM, CloudWatch, Lambda — comfortable in the console and with the CLI 
• Experience defining and working within CI/CD pipelines using Jenkins and/or GitHub Actions 
• Python scripting for operational automation 
• Experience working within a formal change management process: CRs, maintenance windows, approvals 
• Clear communicator when things break — you keep stakeholders informed without being asked 
• Comfortable working async across time zones in a distributed team 
• Familiar with AI tools and comfortable using them in day-to-day work 

Nice to Have 

• Apache Airflow — DAG monitoring and operational support 
• MSK / Kafka operational experience 
• Infrastructure as Code experience — Terraform or similar 
• Prometheus & Grafana for monitoring and dashboards 

What’s in it for you?
Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr!

Enjoy NICE-FLEX! 
At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10732
Reporting into: Manager
Role Type: Individual Contributor

About Bold Business

Bold Business is an AI-first U.S.-based company building automation systems, AI agents, and production software for clients like AT&T, JP Morgan, and Verizon. We ship real systems that deliver impact — not experiments.

The Role

We’re hiring a Senior Python Engineer who can own both backend systems and the data layer behind them. This role sits between backend and data — you will build APIs, design pipelines, and ensure the data powering AI systems is clean and reliable.

You’ll work under a Lead Architect. You are expected to execute independently and own outcomes.

What You’ll Do

• Build and maintain production Python APIs (FastAPI or similar)
• Design and run data pipelines (ETL, ingestion, transformation)
• Own data quality — validation, monitoring, failure handling
• Structure data for RAG systems and AI agents
• Design and manage databases (PostgreSQL + vector DBs)
• Integrate external systems (APIs, webhooks, third-party tools)
• Debug across backend, data pipelines, and AI outputs

Non-Negotiables (Knockout Requirements)

You should not apply if you cannot clearly demonstrate all of the following:

1. Strong English communication (written and spoken)
   You can clearly explain technical concepts to non-technical stakeholders and operate in a U.S.-based team environment.
2. You have built and maintained production Python APIs
   (not tutorials or small scripts — real systems in use)
3. You have owned data pipelines end-to-end
   (ingestion → transformation → reliability in production)
4. You are strong in SQL and database design
   (schemas, performance, tradeoffs — not just basic queries)
5. You have worked with real, messy data
   (multiple sources, failures, edge cases — not clean datasets)

Required Skills

• Python (4–6 years, production backend + data work)
• FastAPI or similar frameworks
• Strong SQL and database design
• API integrations (REST, webhooks)
• Testing and clean Git workflows

AI / Data Context (Expected Working Level)

• LLM API integration (OpenAI, Anthropic, etc.)
• Understanding of how RAG systems use data
• Prompt structure and output handling
• Exposure to vector databases (pgvector, Pinecone, etc.)

Nice to Have

• LangChain, LangGraph, CrewAI
• Airflow, Prefect, or pipeline orchestration
• AWS / GCP experience
• Docker / CI-CD
• Basic BI / analytics tools

What This Role Is

• A hands-on builder role
• Ownership of backend + data layer
• High accountability, low hand-holding

What This Role Is Not

• Not a pure Data Engineer
• Not an ML research role
• Not a junior position

Final Note

• We will go deep into your past work.
• If you can clearly explain what you built, why you built it that way, and what broke — you’ll do well here.
• If not, this role will be a stretch.

Bold Business — AI-First. Delivery-First.