Job Summary:
Gen AI
This role requires strong communication and leadership skills, with the ability to translate complex technical requirements into actionable plans and ensure successful, timely, and high-quality delivery with attention to details.
Key Responsibilities:
Project & Program Delivery
- Manage end-to-end, the full lifecycle of data engineering and analytics, projects including data platform migrations, dashboard/report development, and advanced analytics initiatives.
- Define project scope, timelines, milestones, resource needs, and deliverables in alignment with stakeholder objectives.
- Manage budgets, resource allocation, and risk mitigation strategies to ensure successful program delivery.
- Use Agile, Scrum, or hybrid methodologies to ensure iterative delivery and continuous improvement.
- Monitor performance, track KPIs, and adjust plans to maintain scope, schedule, and quality.
- Excellence in execution and ensure client satisfaction
Client & Stakeholder Engagement
- Serve as the primary point of contact for clients and internal teams across all data initiatives.
- Translate business needs into actionable technical requirements and facilitate alignment across teams.
- Conduct regular status meetings, monthly and quarterly reviews, executive updates, and retrospectives.
Manage Large teams
- Ability to manage up to 50+ resources working on different projects for different clients.
- Work with practice and talent acquisition teams for resourcing needs
Manage P & L
- Manage allocation, gross margin, utilization etc effectively
Team Coordination
- Lead and coordinate cross-functional teams including data engineers, BI developers, analysts, and QA testers.
- Ensure appropriate allocation of resources across concurrent projects and clients.
- Foster collaboration, accountability, and a results-oriented team culture.
Data, AI and BI Technology Oversight
- Manage project delivery using modern cloud data platforms
- Oversee BI development using Tableau and/or Power BI, ensuring dashboards meet user needs and follow visualization best practices. Conduct UATs
- Manage initiatives involving ETL/ELT processes, data modeling, and real-time analytics pipelines.
- Ensure compatibility with data governance, security, and privacy requirements.
- Manage AL ML projects
Data & Cloud Understanding
- Oversee delivery of solutions involving cloud data platforms (e.g., Azure, AWS, GCP), data lakes, and modern data stacks.
- Support planning for data migrations, ETL processes, data modeling, and analytics pipelines.
- Be conversant in tools such as Power BI, Tableau, Snowflake, Databricks, Azure Synapse, or BigQuery.
Risk, Quality & Governance
- Identify and mitigate risks related to data quality, project timelines, and resource availability.
- Ensure adherence to governance, compliance, and data privacy standards (e.g., GDPR, HIPAA).
- Maintain thorough project documentation including charters, RACI matrices, RAID logs, and retrospectives.
Qualifications:
- Bachelor’s degree in Computer Science, Information Systems, Business, or a related field.
Certifications (Preferred):
- PMP, PRINCE2, or Certified ScrumMaster (CSM)
- Cloud certifications (e.g., AWS Cloud Practitioner, Azure Fundamentals, Google Cloud Certified)
- BI/analytics certifications (e.g., Tableau Desktop Specialist, Power BI Data Analyst Associate, DA-100)
Must Have Skills:
- Strong communication skills
- Strong interpersonal
- Ability to work collaboratively
- Excellent Organizing skills
- Stakeholder Management
- Customer Management
- People Management
- Contract Management
- Risk & Compliance Management
- C-suite reporting
- Team Management
- Resourcing
- Experience using tools like JIRA, MS Plan etc.
Desirable Skills:
- 15 years of IT experience with 8+ years of proven project management experience, in delivering data, AI Ml, BI / analytics-focused environments.
- Experience delivering projects with cloud platforms (e.g., Azure, AWS, GCP) and data platforms like Snowflake.
- Proficiency in managing BI projects preferably Tableau and/or Power BI.
- Knowledge or hands on experience on legacy tools is a plus.
- Solid understanding of the data lifecycle including ingestion, transformation, visualization, and reporting.
- Comfortable using PM tools like Jira, Azure DevOps, Monday.com, or Smartsheet.
- Experience managing projects involving data governance, metadata management, or master data management (MDM).
