About the role

Job Description: Data Engineering Project Manager

Role Overview

A hybrid role combining project/program management with hands-on data engineering capability. Approximately 50% of the role is project leadership and coordination; the remaining ~50% is expected to be spent contributing directly to data engineering workstreams. This is not a pure project coordinator role, and it is explicitly not a Scrum Master position.

Key Responsibilities

Project Leadership & Coordination (~60%)

Build and maintain project plans across multiple workstreams and use cases
Identify risks and proactively surface conflicts; help resolve them
Readjust plans as new priorities or urgent items arise
Keep Jira boards updated and keep stakeholders informed
Track reprioritization explicitly — e.g., communicating clearly when only 4 of 10 planned items were completed and why, with an updated timeline
Lead and coordinate “foundational” initiatives that sit outside standard projects or BAU work (e.g., internal tooling upgrades, GenAI agent builds) — ensuring this work has a bounded plan and timeline rather than running open-ended
Advise on lightweight agile practices: the team works in a loose 2-week sprint cadence (most initiatives actually span 6–8 weeks), and the person should help right-size ceremonies (e.g., questioning whether daily standups are needed vs. meeting every 2 days)

Data Engineering Contribution (~40%, primarily during lean periods)

Contribute directly to day-to-day data engineering work streams
Use engineering credibility to question and challenge estimates (e.g., pushing back on a “3-week” estimate) — including with senior/full-time team members — which requires a genuine engineering background to do with confidence

Ideal Candidate Profile

10 years of experience in project/program/delivery management roles
Background in data engineering, with experience on large-scale data transformation and environments processing large data volumes
Prior experience in an agile environment (understands sprint cadences and the pitfalls of over-processing, e.g., excessive meetings) — but this is not a Scrum Master role
Strong communicator, comfortable driving clarity across BAU work, project work, and foundational/innovation work simultaneously
Senior enough to operate across multiple teams and multiple use cases
Comfortable in a modern engineering environment (team uses Claude Code, GitHub, etc.)
Technical proficiency in working with Python, Pyspark, SQL, Hadoop, Hive, Airflow, on-prem infrastructure, scheduler, etc.

Location & Work Arrangement

Based in India, preferred location Bangalore
Hybrid: onsite roughly 2-3 days per week, remainder remote. But this is preferred and not mandatory
Target start date: first week of October (but need the candidate identified by mid-September to start the onboarding process).

Interview Process:

Candidate will be interviewed by clients and there will be 2 rounds. (one conducted by onshore and one by Offshore client resource)

Onshore- Chandra Akella,
Offshore- Subir chatterjee
Key EXL resource to leverage for the TR2 and client prep rounds – Laxmi Agrawal. (India based)