MLOps & DataOps Manager

Position Overview

We are looking for a visionary and highly technical DataOps & MLOps Manager to lead our growing data and AI infrastructure teams. In this role, you will bridge the gap between cutting-edge data engineering, robust operations, and advanced artificial intelligence.

You will lead the strategic design of our next-generation ingestion mechanisms and oversee the lifecycle of high-value Data Products—ranging from core analytical datamarts to traditional Machine Learning, Generative AI, and Autonomous Agents. If you are passionate about automation, cloud architecture, and scaling AI capabilities within a modern data ecosystem, we want to hear from you.

Key Responsibilities

• Strategic Leadership: Define the vision, roadmap, and execution strategy for both the DataOps and AIOps teams, ensuring alignment with overall business objectives.
• Data Product Lifecycle: Oversee the end-to-end creation, deployment, and maintenance of diverse Data Products, including Datamarts, Tableau dashboards, traditional ML models, GenAI solutions, and AI agents.
• Ingestion Strategy: Design and optimize scalable, reliable, and secure data ingestion mechanisms for both streaming and batch processing.
• Infrastructure as Code (IaC): Champion automation by ensuring all cloud infrastructure is fully automated, repeatable, and version-controlled.
• CI/CD & Operational Excellence: Establish and enforce rigorous CI/CD practices to ensure seamless, automated deployments, minimizing downtime and maximizing team velocity.
• Team Mentorship: Lead, mentor, and grow a high-performing team of engineers, fostering a culture of continuous learning, agility, and innovation.

Requirements

Required Technical Skills & Qualifications

Cloud & Infrastructure

• AWS Expertise: Deep production experience with AWS data and AI ecosystems, specifically:
• Data Governance & Orchestration: AWS DataZone, AWS Glue, Athena, EMR Serverless.
• Streaming & Messaging: AWS Kinesis.
• AI/ML & GenAI: AWS SageMaker, AWS Bedrock (including experience with foundation models and AI Agents).

DevOps, DataOps & AIOps

• Infrastructure as Code (IaC): Advanced proficiency with Terraform and AWS CDK (Cloud Development Kit).
• CI/CD: Deep expertise in designing and managing complex pipelines using GitLab CI/CD.
• Operations: Strong understanding of monitoring, logging, and alerting frameworks tailored for data pipelines and ML models in production.

Data & Analytics

• Proven experience building scalable Datamarts and integrating modern BI tools like Tableau.
• Solid understanding of data modeling architectures (Data Mesh, Lakehouse, Star Schema).

Leadership & Experience Requirements

• Experience: 6+ years of experience in Data/Platform Engineering, DevOps, or MLOps, with at least 2+ years in a leadership or managerial role.
• AI/ML Familiarity: Strong conceptual and practical understanding of the entire ML lifecycle (from feature stores to model monitoring) as well as the unique operational challenges of Large Language Models (LLMs) and GenAI.
• Agile Mindset: Proven track record of managing teams using Agile/Scrum methodologies.
• Communication: Exceptional communication skills with the ability to translate complex technical architectures into strategic business value for stakeholders.

Why Join Us?

• Cutting-Edge Tech Stack: Work directly with the latest cloud, GenAI, and agentic technologies.
• High Impact: Shape the data and AI foundation that drives our company's core business decisions.
• Growth Culture: Lead a talented, collaborative team in an environment that prioritizes innovation and professional development.