Technical Project Manager

Saras Analytics · India

About the Role

Saras Analytics is looking for a Technical Project Manager to drive delivery governance across its

Consulting team. This role sits at the intersection of client engagement management and technical

execution — coordinating with Engagement Leads, Data Engineering pods, and cross-functional teams

to ensure every client use case is delivered on time, with full visibility into risks and blockers.

The TPM will not just manage process — they will own delivery outcomes. That means understanding

what the client is trying to achieve (e.g., average order value trends, sales performance dashboards),

translating those into realistic project plans, and proactively flagging when timelines need adjustment

before commitments are broken.

What You Will Do

Project Planning & Sprint Management

● Own end-to-end project plans for consulting engagements — from client onboarding and

charter creation through milestone tracking to final delivery.

● Build and maintain sprint cycles (typically 2-week cadence) with clear goals, backlogs, and

acceptance criteria for each sprint.

● Run sprint planning, sprint review, and retrospective calls with Engagement Leads and relevant

team leads.

● Maintain project workspaces in ClickUp (or equivalent tools) with consistent structure, fields,

and governance — ensuring cross-team visibility without redundant or conflicting data.

Delivery Ownership & Risk Management

● Track progress across all active consulting engagements and flag delays before they surface as

client escalations.

● Engage with Engagement Leads to validate timeline estimates — push back when scopes are

underestimated, and get commitments adjusted proactively.

● Coordinate dependencies across consulting, data engineering, and engineering/infrastructure

teams to unblock execution.

● Maintain a clear view of what each client is at, what stage their delivery is in, and what the next

sprint goal is at any point in time.

Stakeholder Communication

● Serve as the central coordination point between Engagement Leads and Data Engineering pods

— translate consulting asks into actionable technical tickets with proper acceptance criteria.

● Present bi-weekly delivery status updates to internal stakeholders; communicate sprint goals

and upcoming milestones clearly.

● Over time, participate in client-facing demos and delivery reviews (bi-weekly cadence),

representing project status and next sprint goals.

Process Governance & Adoption

● Drive adoption of standardised project management processes across consulting pods —

including ticket templates, milestone definitions, and sprint hygiene.

● Create and maintain process documentation for delivery workflows, escalation paths, and

onboarding playbooks for new team members.

● Conduct onboarding sessions for new joiners covering e-commerce domain basics, connector

landscape, and cross-team workflows.

What We Are Looking For

Must-Have

● 3–6 years of experience in project/program management, preferably in a data, analytics, or

tech services environment.

● Demonstrated ability to run Agile/Scrum workflows — sprint planning, backlog management,

retrospectives — with cross-functional teams.

● Strong coordination skills across multiple concurrent projects and stakeholders with competing

priorities.

● Experience working with project management tools (ClickUp, Jira, Asana, or similar) and the

discipline to enforce governance without losing team buy-in.

● Enough domain fluency to understand what a client ask involves technically — you don't need

to build dashboards, but you should understand what makes an average-order-value analysis

more or less complex.

Good to Have

● Familiarity with e-commerce and retail analytics concepts — connectors (Shopify, Amazon,

etc.), BI layers, data pipelines.

● Experience managing delivery in a consulting or client-services environment where expectations

are set externally.

● Comfort with client-facing communication — status updates, demos, expectation management.

● Understanding of data engineering workflows: connectors, data modelling, QA/certification,

and dashboard/presentation layers.

What Success Looks Like

● No client commitment is broken because a timeline risk wasn't caught early enough.

● Engagement Leads spend less time chasing cross-team dependencies and more time on delivery

quality.

● Sprint velocity and milestone adherence are trackable, visible, and consistently improving.

● New hires on the consulting team understand how delivery works within the first two weeks.

● ClickUp (or equivalent) is a single source of truth — not a contested, noisy system that people

work around.