VP Business Intelligence

Role Description

About TresVista

TresVista is a global enterprise whose business model is built to deliver enduring value. TresVista combines best practices, technology enabled execution, and industry-leading talent to drive meaningful results. By integrating advisory capabilities with scalable delivery, TresVista helps clients operate smarter and grow stronger. TresVista's services include investment diligence, industry research, valuation, fund administration, accounting, and data analytics.

Overview

This role will be responsible for managing the execution of Business Intelligence projects with an objective to enable data-driven decision-making and improve operational efficiency of the organization. You will ensure implementation of projects as per strategic roadmap in terms of timelines and agreed architecture and to achieve this, you are expected to possess right balance of technical and functional expertise. This role demands a focus to drive automation, data governance and data intelligence initiatives across the organization through collaboration among the business units, vendors and a high-performance team of Data Engineers, Data Scientists and Data Analysts to meet the delivery objectives.

Roles And Responsibilities

Program Management in Business Intelligence (Project Delivey, Crossfunctional collaboration and Stakeholder Management):

• Experience leading large scale data platform and data lake implementation initiatives.
• Manage data delivery and quality using defect life cycle and ensure complete tracking and closure involving responsible entities in the organization
• Working experience in Data Engineering and Anaytics. Understanding of Data Science and Machine Learning.
• Collaborate with business units and other functions to understand their KPIs/decision/visualization needs and define project lifecycles for these needs
• Foster a collaborative environment among business units, leadership, in-house Business Intelligence team, and vendors with a purpose to understand requirements, define use cases, translate into technical scenarios and deliver measurable end-results.
• Manage delivery of projects using Agile/DevOps practices
• Ability to drive execution within teams by dividing larger work units into measurable user stories
• Define milestones and KPIs across project phases to measure project velocity
  
  

Prerequisites

• 5+ year of experience with designing and implementing Data Engineering and ETL and solutions.
• Good understanding of Data Science and Visualization tools.
• Working experience in data intelligence ecosystem on any of the clouds (AWS, Azure and GCP). AWS ecosystem is preferred.
• Working Knowledge of tools like Python, SQL, PowerBI, Tableau etc.
• Solid expertise in managing IT programs using standard Agile delivery practices and DevOps/DevSecOps based approach.
• Ability to deliver in a multi-stakeholder environment
• Knowledge of experimentation and deployment life cycle of Data Science, Machine Learning and Generative AI
• Understanding of Data models, ETL, Data Governance, Metadata Management etc.
• Knowledge of Machine Learning Operations (MLOps)
• Good presentation skills and ability to articulate solutions, designs, processes and project deliverables clearly
• Strong techno-functional mindset
  
  

Experience

• 10+ years of overall IT experience with atleast of 5 years experience in managing the delivery of projects involving data. Experience with delivery of Data Science projects would be a plus.
• Excellent leadership, communication, and collaboration skills
• 5+ years of experience with project planning, project delivery, team/stakeholder management
• Proven ability to align Data and AI initiatives with business goals and deliver measurable outcomes
• Experience in managing data quality, lineage, data security, unified access control
• Strategic thinking, design thinking, problem-solving, and a strong team player.
  
  

Education

• A Bachelor/Master degree from a Tier I institute or a Ph.D. in data science, computer science, statistics, or a related quantitative field is preferred.
  
  

Compensation

The compensation structure will be as per industry standards