Job Description

Primary Responsibilities

Cloud Infrastructure & Operations

• Manage, scale, and optimize cloud environments used for data science workloads (primarily AWS, Databricks, dbt).
• Provision, maintain, and optimize compute clusters for ML workloads (e.g., Kubernetes, ECS/EKS, Databricks, SageMaker).
• Implement and maintain high-availability solutions for mission-critical analytics platforms.
• Deep expertise in AWS resource management and provisioning, including IAM roles and permissions.

DevOps & Automation

• Develop CI/CD pipelines for model deployment, infrastructure-as-code (IaC), and automated testing using industry standard toolchains
• Build monitoring, alerting, and logging systems for cloud and ML infrastructure (e.g., Datadog, CloudWatch, Prometheus, Grafana, ELK).
• Automate provisioning, configuration, and deployments using tools such as Terraform and CloudFormation, GitHub actions, etc.

Security, Compliance & Governance

• Implement and operationalize data science security and compliance controls for data science platforms in alignment with enterprise cloud standards.
• Conduct periodic risk assessments,best practice reviews, and remediation efforts to strengthen security and resiliency.
• Support secure handling of sensitive financial data.

Cross-Functional Collaboration

• Partner with data scientists, machine learning engineers, and data engineers to deeply understand and support their needs and workflows within data-driven initiatives.
• Serve as a technical advisor on cloud architecture, performance optimization, and production readiness for data and ML platforms.
• Adopt and champion Agile, DevOps, and Platform Engineering practices (kanban, scrum, continuous improvement, automation, Everything-as-a-Service)
• Demonstrate a strong, proactive focus on serving internal customers, prioritizing user experience, identifying opportunities to leverage automation and self-service to reduce toil and cognitive load for developers and researchers.

Requirements

Education & Certificates

• A bachelor’s degree or higher in a STEM field, required

Professional Experience

• 5+ years of experience in cloud operations, DevOps, platform engineering, SRE, sysadmin or related roles.
• Strong proficiency with at least one major cloud provider (AWS preferred).
• Hands-on experience with IaC tools (Terraform, CloudFormation, or similar).
• Strong scripting skills (Python, Bash, or PowerShell).
• Strong understanding of modern authentication and authorization technologies and secrets management (IAM, OIDC, OAuth2, RBAC, ABAC, privileged access management, JIT authorization, PKI).
• Experience with common CI/CD systems (GitHub Actions, Jenkins, GitLab CI, ArgoCD,, or similar).
• Familiarity with container orchestration (Docker Compose, EKS/Kubernetes, ECS).
• Experience supporting data-intensive or ML workloads.

Preferred

• Experience in financial services, investment management, or other highly regulated industries.
• Knowledge of ML/AI platform tools (Databricks, SageMaker, MLflow, Airflow).
• Hands-on experience with AI Engineering and LLMOps tools (LLM observability, eval pipelines, building/supporting agentic workflows) are a huge plus.
• Understanding of networking, VPC architectures, and cloud security best practices.
• Familiarity with distributed compute frameworks (Spark, Ray, Dask).

Lead data engineering strategy across projects. Drive innovation in practices and optimization. Represent team in executive meetings. Develop long-term data plans.

Graduate in Computer Science, Data Science, or related field. 4-6 years of experience in data engineering or related field.

EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.