Applications Practice Manager driving customer success and revenue growth at HBS. Leading a high-performing team focused on innovative, customer-centric solutions.
Responsibilities
The Applications Practice Manager plays a pivotal role in driving revenue growth and customer success.
Leading a high-performing team of Team Leads and direct reports.
Responsible for building and nurturing a results-driven organization focused on delivering innovative, customer-centric solutions.
Closely engage with customers to understand their business needs, foster strong relationships, and support the sales process from pre-sales through delivery.
Empowering their team, setting clear performance expectations, and championing best practices.
Ensuring exceptional service delivery while shaping technology strategy and advancing the organization’s market leadership.
Requirements
At least 5 years of experience in the IT Services industry.
A minimum of 5+ years of experience in data management and data analytics.
Proven experience in leading and managing data analytics team.
Experience in developing and deploying data analytics projects.
Experience working with and creating databases and dashboards using all relevant data to inform decisions.
Experience using analytics techniques to contribute to company growth efforts, increasing revenue and other key business outcomes.
Experience with three (3) or more of the following technologies:
• Microsoft Fabric
• Data lake technologies
• Azure Data Factory or other ETL tools
• Databricks
• Microsoft Azure SQL, Azure SQL Data Warehouse / Azure Synapse, Snowflake or Amazon Redshift
• Streaming data ingestion tools
• Visualization tool experience such as Power BI, Tableau, or Qlik
• Analysis Services (SSAS - tabular cubes)
• Machine learning
• C# / ASP.NET
BA/BS degree or higher in Computer Science or a quantitative field (i.e. Statistics, Math, etc.)
Microsoft Certified: Azure Data Scientist Associate or Fabric Engineer Associate
Knowledge of machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
Strong working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources.
Strong SQL skills, ability to perform effective querying involving multiple tables and subqueries.
Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for customers.
Business leadership; management of a dedicated P&L with performance-related goals.
Strong problem solving, quantitative and analytical abilities.
Strong ability to plan and manage numerous processes, people and projects simultaneously.
Exceptional organizational and planning skills.
Excellent communication, collaboration and delegation skills.
Public speaking experience in a professional conference setting.
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