Company Description

JMAN is the commercial data partner that specializes in maximizing value creation activities for private equity funds and their portfolio companies. We partner with our clients to address the growing need for investment decisions and value creation initiatives to be backed by reliable, real-time data. When companies partner with JMAN, we combine our data science and data engineering expertise with our deep commercial understanding to deliver tangible, high-value outcomes at pace. Founded in 2010, JMAN has a global footprint with offices in New York, London and Chennai. Our team of more than 350 experts partner with more than 80 private equity funds and over 200 portfolio companies. Nearly 85% of our business is from recurring partnerships with our clients. JMAN has been a portfolio company of Baird Capital since 2023.

Position

Strong understanding of data engineering and analytics concepts, including ELT/ETL pipelines, data warehousing, and reporting layers.

Experience in ticketing, issue triaging, SLAs, and capacity planning for BAU operations.

Hands-on understanding of SQL and scripting languages (Python preferred) for debugging/troubleshooting.

Proficient with cloud platforms like Azure and AWS; familiarity with DevOps practices is a plus.

Familiarity with orchestration and data pipeline tools such as ADF, Synapse, dbt, Matillion, or Fabric.

Understanding of monitoring tools, incident management practices, and alerting systems (e.g., Datadog, Azure Monitor, PagerDuty).

Strong stakeholder communication, documentation, and presentation skills.

Experience working with global teams and collaborating across time zones.

Requirements

• Serve as the primary owner for all managed service engagements across all clients, ensuring SLAs and KPIs are met consistently.
• Continuously improve the operating model, including ticket workflows, escalation paths, and monitoring practices.
• Coordinate triaging and resolution of incidents and service requests raised by client stakeholders.
• Collaborate with client and internal cluster teams to manage operational roadmaps, recurring issues, and enhancement backlogs.
• Lead a >40 member team of Data Engineers and Consultants across offices, ensuring high-quality delivery and adherence to standards.
• Support transition from project mode to Managed Services including knowledge transfer, documentation, and platform walkthroughs.
• Ensure documentation is up to date for architecture, SOPs, and common issues.
• Contribute to service reviews, retrospectives, and continuous improvement planning.
• Report on service metrics, root cause analyses, and team utilization to internal and client stakeholders.
• Participate in resourcing and onboarding planning in collaboration with engagement managers, resourcing managers and internal cluster leads.
• Act as a coach and mentor to junior team members, promoting skill development and strong delivery culture.