Softomatic Technology Services · Bengaluru
Technical Project Manager – Data & AI
Job Description:
The Technical Project Manager – Data & AI is responsible for planning, executing, and delivering medium to large-scale Data, Analytics, and AI projects within Professional Services or enterprise environments. This role acts as the bridge between business stakeholders and technical delivery teams, ensuring projects are delivered on time, within scope, budget, and quality standards.
The role requires strong technical understanding of Data & AI ecosystems, experience working closely with engineers and data scientists, and the ability to translate business requirements into executable delivery plans. While not expected to be hands-on in development, the role demands deep delivery ownership and day-to-day project execution leadership.
Role Positioning
Individual contributor project leadership role
No direct people management responsibility
Hands-on involvement in project planning, execution, and delivery tracking
Requires technical depth across Data & AI domains, without coding responsibilities
Client-facing role within Professional Services / Consulting / Internal Delivery teams
Mandatory Profile Criteria
4–10 years of experience in Technical Project Management or Delivery Management
Proven experience delivering Data, Analytics, and AI/ML projects
Background in Professional Services, Consulting, System Integration, or Product Delivery
Experience working with cross-functional technical teams (Data Engineers, ML Engineers, BI Developers, Cloud Teams)
Strong client and stakeholder communication skills
Key Responsibilities
1. Project Delivery & Execution
Lead end-to-end delivery of Data & AI projects including Data Engineering, Analytics, BI, AI/ML, and MLOps initiatives.
Own project planning, scope definition, timelines, dependencies, risk management, and execution tracking.
Ensure delivery alignment with agreed architecture, quality standards, and business outcomes.
2. Technical Project Governance
Drive sprint planning, backlog management, milestone tracking, and delivery reviews across Agile or hybrid delivery models.
Identify risks, issues, and dependencies early and drive mitigation plans with technical leads.
Ensure adherence to data governance, security, and compliance requirements.
3. Stakeholder & Client Management
Act as the primary point of contact for clients or internal stakeholders for project-related communication.
Translate complex technical concepts into clear, business-aligned updates for non-technical stakeholders.
Manage expectations and ensure transparency on progress, risks, and changes.
4. Collaboration with Technical Teams
Work closely with Data Engineers, Data Scientists, ML Engineers, Platform Engineers, and Architects.
Support technical teams by removing blockers, clarifying requirements, and ensuring realistic commitments.
Review technical plans, delivery approaches, and solution designs from a feasibility and risk perspective.
5. Pre-Sales & Planning Support (as required)
Support solution shaping, effort estimation, and delivery planning during pre-sales or project initiation phases.
Contribute to identifying risks, assumptions, and dependencies during proposal or SOW creation.
6. Delivery Excellence & Continuous Improvement
Apply best practices in Agile, Scrum, or hybrid delivery frameworks.
Capture lessons learned and contribute to continuous improvement of delivery processes and standards.
Technical Knowledge Expectations
Strong understanding of:
Data Engineering & Data Pipelines
Cloud data platforms (Azure, AWS, or GCP)
Analytics & BI solutions
AI/ML lifecycle and MLOps concepts
Data governance, security, and privacy principles
Ability to engage confidently with architects and engineers on technical discussions without hands-on coding.
Education & Certifications
Bachelor’s degree (Engineering, Computer Science, or related field preferred)
PMP / PRINCE2 / Agile or Scrum certification Mandate
Cloud or Data-related certifications (Azure, AWS, Databricks, etc.) are a plus
Ideal Candidate Profile
Technically savvy project manager who enjoys working close to engineering teams
Strong organizer with excellent communication and stakeholder management skills
Comfortable managing ambiguity in fast-paced Data & AI delivery environments
Passion for driving business value through data and AI initiatives
Education & Certifications
Bachelor’s degree (Engineering, Computer Science, or related field preferred)