Leadership Role - Data Analytics + Managed Services

Job Requirements and Preferences:

• Minimum Degree Required: Bachelors degree in information technology, Data Science, Computer Science, Statistics, or a related field (Masters degree preferred)
• Minimum Years of Experience:
• 14 year(s) with at least 3 years in a managerial or leadership role.
• Proven experience in managing data analytics services for external clients, preferably within a managed services or consulting environment
• Technical Skills: Experience and knowhow of working with a combination/subset tools and technologies listed below
• Proficiency in data analytics tools (e.g., Power BI, Tableau, QlikView), Data Integration tools (ETL, Informatica, Talend, Snowflake etc.) and programming languages (e.g., Python, R, SAS, SQL).
• Strong understanding of Data & Analytics services cloud platforms (e.g., AWS, Azure, GCP) like AWS Glue, EMR, ADF, Redshift, Synapse, BigQuery etc and big data technologies (e.g., Hadoop, Spark).
• Familiarity with traditional Datawarehousing tools like Teradata, Netezza etc
• Familiarity with machine learning, AI, and automation in data analytics.
• Certification in data-related disciplines preferred

• Leadership:

  Demonstrated ability to lead teams, manage complex projects, and deliver results.

• Communication:

  Excellent verbal and written communication skills, with the ability to present complex information to non-technical stakeholders

Roles & Responsibilities:

• Demonstrates intimate abilities and/or a proven record of success as a team leader, emphasizing the following:

Client Relationship Management:

Serve as the focal point for level client interactions, maintaining strong relationships.

Manage client escalations and ensure timely resolution of issues.

Face of the team for strategic client discussions, Governance and regular cadence with Client

Service Delivery Management:

Responsibly Lead end-to-end delivery of managed data analytics services to clients, ensuring projects meet business requirements, timelines, and quality standards

Deliver Minor Enhancements and Bug Fixes aligned to client’s service delivery model

Good Experience setting up Incident Management, Problem Management processes for the engagement

Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to deliver end-to-end solutions

Monitor, manage & report service-level agreements (SLAs) and key performance indicators (KPIs).

Solid financial acumen with experience in budget management.

Problem-solving and decision-making skills, with the ability to think strategically

Operational Excellence & practice growth:

Implement and oversee standardized processes, workflows, and best practices to ensure efficient operations.

Utilize tools and systems for service monitoring, reporting, and automation to improve service delivery.

Drive innovation and automation in data integration, processing, analysis, and reporting workflows

Keep up to date with industry trends, emerging technologies, and regulatory requirements impacting managed services.

Risk and Compliance:

Ensure data security, privacy, and compliance with relevant standards and regulations

Ensure all managed services are delivered in compliance with relevant regulatory requirements and industry standards.

Proactively identify and mitigate operational risks that could affect service delivery.

Team Leadership & Development:

Lead and mentor a team of service managers and technical professionals to ensure high performance and continuous development.

Foster a culture of collaboration, accountability, and excellence within the team.

Ensure the team is trained on the latest industry best practices, tools, and methodologies.

Capacity Management, experience with practice development, strong understanding of agile practices, cloud platforms, and infrastructure management

Pre-Sales Experience:

Collaborate with sales teams to identify opportunities for growth and expansion of services.

Experience in solutioning of responses and operating model including Estimation frameworks, content contribution, solution architecture in responding to RFPs