DEPARTMENT: BUSINESS INTELLIGENCE / DATA

ABOUT XTENDOPS

XO delivers outsourced customer experience and business operations, built on operational excellence, AI-driven innovation, and a bold approach to problem-solving. We help companies run smarter, operate more efficiently, and drive measurable business impact.

We are in the middle of a massive evolution, expanding beyond traditional outsourcing into a next-generation model that integrates AI, automation, and SaaS-driven solutions to deliver outcome-focused business services. Our vision is not just to improve CX. It is to reinvent how businesses leverage technology, data, and human expertise to create intelligent, scalable, and revenue-generating service models.

MAIN JOB OBJECTIVE:

The Project Manager — Data & Analytics runs the team's two scaling efforts, expanding data modeling and reporting delivery across a growing number of client accounts, and building the delivery path that pushes modeled data into the internal software platform, as structured, sprint-driven programs rather than a stream of ad-hoc requests. Day-to-day execution runs on Scrum, layered with phase-gated milestone planning for multi-quarter platform initiatives and client-facing commitments.

This is a hands-on delivery role. It does not involve writing production data models or application code, but does require reading a pipeline dependency graph, understanding what a data model is, and holding a technical conversation with an engineer without a translator.

RESPONSIBILITIES AND MAIN ACTIVITIES

Agile / Scrum Delivery:

- Own the Scrum cadence end to end for a team spanning data engineering, analytics engineering, software development, and analytics: sprint planning, daily standups, backlog refinement, sprint reviews, and retrospectives.
- Act as Scrum Master in practice, protecting the sprint from mid-sprint scope injection, removing impediments, and coaching the team on Agile discipline where habits are still ad-hoc.
- Maintain a healthy, groomed, estimated backlog with clear definition-of-ready and definition-of-done, sizing and slicing stories so they can finish inside a sprint.
- Track and use delivery metrics, including velocity, sprint burndown, cycle time, carryover, and escaped defects, to forecast credibly and drive retrospective actions that change how the team works.
- Run the hybrid layer, mapping sprint output onto phase-gated milestones for platform initiatives and client commitments so short-cycle iteration and long-horizon dates stay reconciled.
- Adapt the process to the work: Scrum for product and modeling delivery, Kanban-style flow for operational and support requests, and phase gates for migrations and client cutovers.
- Continuously improve the operating model and raise team maturity in estimation, story writing, and predictable delivery.

Roadmap and Program Ownership:

- Own the consolidated delivery roadmap covering platform initiatives and client reporting work, keeping it current, sequenced, and visible to stakeholders.
- Drive multi-phase rollouts from pilot through full deployment, tracking scope, dependencies, and clear exit criteria for each phase.
- Break large initiatives into deliverable increments with named owners, acceptance criteria, and dates, and identify the critical path and the dependencies that will break it.




- Keep the team's architectural decision record current so decisions are written down, discoverable, and not relitigated.

Intake and Prioritization:

- Run a single intake process for all data, dashboard, and reporting requests coming from operations leaders, account teams, and the product side.
- Triage and prioritize against business impact, effort, and available capacity, saying no or not-yet credibly with reasoning stakeholders can accept.
- Protect engineering focus by batching requests, eliminating duplicates, and preventing direct-to-engineer side channels from becoming the default.

Cross-Team Delivery and Hand-offs:

- Coordinate hand-offs along the full data path, including ingestion, modeling, publishing, and application delivery, where each stage has a different owner and skill set.
- Track and unblock work: surface risks early, escalate with a recommendation rather than just a problem, and keep blocked work from sitting silently.
- Coordinate release and migration work with product and engineering counterparts, including cutover plans and rollback paths.

Stakeholder Management:

- Act as the primary point of contact between the data team and operations leadership, account teams, and product stakeholders.
- Translate in both directions: business requirements into technical scope engineers can act on, and technical constraints into trade-offs business stakeholders can decide on.
- Run regular program reviews and status reporting, keeping leadership informed with honest, concise updates rather than dashboards nobody reads.
- Support client-facing commitments around data scope, freshness expectations, and what the team will and will not promise.

SLAs, Cost, and Quality:

- Define and track delivery and data SLAs, including pipeline freshness, refresh cadence, incident response, and request turnaround.
- Monitor and report cloud spend across the data and application stack, ensuring budgets, usage alerts, and quotas are in place and acted upon.
- Treat data freshness as a deliberate decision per report rather than a default, since refresh frequency is a primary cost driver in cloud data platforms.
- Partner with engineering on test coverage, freshness and anomaly monitoring, and incident post-mortems, making sure findings turn into backlog items.

Team Scaling:

- Support a phased hiring plan as the team grows, including role scoping, interview coordination, and onboarding plans.
- Track team capacity and utilization against account load, flagging early when delivery commitments exceed available capacity.

QUALIFICATIONS AND EXPERIENCE

- 3–5 years of project, program, or delivery management experience on technical teams (data, analytics, platform, or software engineering), with at least part of that time managing engineers directly as a PM rather than only coordinating vendors or business projects.
- Substantial hands-on Scrum experience required: personally running the full ceremony set across many consecutive sprints, owning a backlog, facilitating retrospectives, and using velocity and burndown data to forecast.



Scrum Master or equivalent time-in-seat strongly preferred.
- Proven hybrid-methodology delivery, combining Agile execution with phase-gated or milestone-based planning on the same program, and able to explain concretely how the two were kept honest with each other.
- Working knowledge of more than one Agile framework and the judgment to pick per workstream: Scrum for product delivery, Kanban or Scrumban for support and operational request flow, phase gates for migrations.
- Demonstrated ownership of a multi-phase technical program from planning through delivery, including managing dependencies across more than one team.
- Working data literacy: able to explain what a data warehouse, a pipeline, an ETL/ELT job, and a data model are; able to read a pipeline dependency graph and understand what depends on what; comfortable with basic SQL.
- Fluency configuring and running Agile boards, sprints, and reporting in a work-management tool such as ClickUp, Jira, Azure DevOps, Asana, or Linear.
- Strong stakeholder management: able to hold a line on priorities with a senior stakeholder, and deliver bad news early and clearly.
- Excellent written communication in English, since much of this role is writing status updates, requirements, decision records, and escalations.
- Comfort operating with ambiguity and incomplete information, and the judgment to know when to decide versus when to escalate.

PREFERRED

- Scrum certification (CSM, PSM I/II, or PSPO) is a strong plus, as is PMI-ACP, PMP, or SAFe for the hybrid and phase-gated side. Track record outweighs certification, but the vocabulary and rigor behind it are expected.
- Experience introducing or maturing Agile practice on a team that was previously running ad-hoc.
- Experience applying Agile to data work specifically, where "done" is a tested data model or pipeline rather than a shipped interface feature.
- Experience in a BPO, outsourcing, or shared-services environment, or otherwise managing delivery across multiple client accounts simultaneously.
- Familiarity with a modern data stack: a cloud warehouse such as Snowflake, BigQuery, Redshift, or Databricks; transformation tooling such as dbt; and workflow orchestration such as Airflow.
- Exposure to cloud cost management or FinOps: budgets, spend attribution, usage monitoring.
- Enough understanding of web application delivery (APIs, caching, deployment) to coordinate a data-to-application delivery path.
- Familiarity with data governance topics relevant to client-facing analytics: tenant isolation, role-based access control, and PII handling.
- Experience coordinating BI and reporting delivery with tools such as Tableau, Power BI, or Looker.
- Prior involvement in scaling a team: hiring loops, onboarding, capacity planning.

AVAILABILITY

- Full-time, remote, with overlap required across North America and Asia-Pacific business hours.

SKILLS

- Scrum Facilitation and Agile Coaching
- Hybrid (Agile + Phase-Gated) Program Management
- Backlog Management and Estimation
- Delivery Metrics and Forecasting (Velocity, Burndown, Cycle Time)
- Intake and Prioritization
- Cross-Team Coordination and Dependency Management
- Stakeholder Management and Executive Communication
- SLA and Cost Tracking
- Working Data Literacy (Pipelines, Warehousing, SQL)
- Documentation and Decision Records
- Team Capacity Planning

📌 Project Manager - Data and Analytics (México)
🏢 XtendOps
📍 México