Job
Description
About the Company JMAN Group is a growing technology-enabled management consultancy that empowers organizations to create value through data. Founded in 2010, we are a team of 450+ consultants based in London, UK, and a team of 300+ engineers in Chennai, India. Having delivered multiple projects in the US, we are now opening a new office in New York to help us support and grow our US client base. We approach business problems with the mindset of a management consultancy and the capabilities of a tech company. We work across all sectors, and have in depth experience in private equity, pharmaceuticals, government departments and high-street chains. Our team is as cutting edge as our work. We take pride for ourselves on being great to work with – no jargon or corporate-speak, flexible to change and receptive of feedback. We have a huge focus on investing in the training and professional development of our team, to ensure they can deliver high quality work and shape our journey to becoming a globally recognised brand. The business has grown quickly in the last 3 years with no signs of slowing down. About the Role 7+ years of experience in managing Data & Analytics service delivery, preferably within a Managed Services or consulting environment. Responsibilities 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. Qualifications ETL or ELT: Azure Data Factory, Databricks, Synapse, dbt (any two – Mandatory). Data Warehousing: Azure SQL Server/Redshift/Big Query/Databricks/Snowflake (Anyone - Mandatory). Data Visualization: Looker, Power BI, Tableau (Basic understanding to support stakeholder queries). Cloud: Azure (Mandatory), AWS or GCP (Good to have). SQL and Scripting: Ability to read/debug SQL and Python scripts. Monitoring: Azure Monitor, Log Analytics, Datadog, or equivalent tools. Ticketing & Workflow Tools: Freshdesk, Jira, ServiceNow, or similar. DevOps: Containerization technologies (e.g., Docker, Kubernetes), Git, CI/CD pipelines (Exposure preferred). Required Skills 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.
