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.
- 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)
- 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
Job description provided by EXL Service.
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