Analytics Engineer

ANALYTICS ENGINEER

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 Analytics Engineer owns data modeling for a portfolio of client accounts and builds the shared metric models that every account depends on. This role consolidates core contact center metrics onto master dimensions and shared definitions so that onboarding a new client becomes largely a configuration exercise, while also building the data layer behind a client-facing analytics product. This is a hands-on modeling role, focused on production data models rather than infrastructure, orchestration, or CI configuration.

RESPONSIBILITIES AND MAIN ACTIVITIES

Account Modeling and Delivery:

• Own data modeling for a portfolio of small, medium, and large client accounts, from ingested source data through to serving-ready output.
• Onboard new accounts through the standard scaffolding, and improve that scaffolding along the way.
• Deliver and support the recurring reporting those accounts depend on, working with the analyst assigned to each account.
• Diagnose and fix data issues in owned models, including tracing a wrong number back through the transformation chain to its source.

Shared Metric Foundation:

• Build and maintain the core metric models shared across all accounts: handle time, CSAT, quality scores, first contact resolution, SLA attainment, and workforce measures such as login time, break time, and worked hours.
• Contribute to the master and conformed dimensions that let the same logic serve clients running different source systems, including the mapping from client-specific source values to master definitions.
• Maintain the master metric dictionary alongside the analyst team: what each metric means, at what grain, with what exclusions, and a worked example.
• Propose the shared version where a requested metric already exists in shared form.

Quality and Contracts:

• Write tests as part of the modeling work, covering both structure and business logic.
• Apply model contracts and versioning on outputs that downstream consumers depend on, so a breaking change is caught in CI rather than in a client's report.
• Take part in freshness and anomaly monitoring for owned models, and in incident post-mortems.

Working with Analysts:

• Review modeling contributions from analysts and raise the standard of what comes through.
• Translate requirements that arrive as a spreadsheet and a conversation into a specification that can be built and tested.
• Ask the questions that prevent the wrong thing being built: what decision does this metric support, at what grain, and what should it exclude.

Documentation and Sprint Delivery:

• Write and maintain documentation and runbooks for owned accounts and models, to the standard that someone else can operate them.
• Work within the team's sprint cadence: sized stories, planning, review, retrospective, and a definition of done that includes tests and documentation.
• Contribute to architectural decision records when a modeling decision is worth writing down.

QUALIFICATIONS AND EXPERIENCE

• 3–5 years in analytics engineering, data engineering, or a BI role with substantial hands-on data modeling.
• Hands-on dbt experience required: models, sources, tests, refs, and a practical grasp of materializations and incremental strategies.
• Strong SQL, including window functions, complex aggregation, and the ability to reason about query performance and cost.
• Dimensional modeling fundamentals: facts, dimensions, and grain.
• Testing discipline, with the ability to explain what a test is protecting against.
• Git and pull-request workflow, comfortable giving and receiving review on SQL.
• Working data literacy beyond own layer: ability to read a pipeline dependency graph and understand what depends on what.
• Enough Python to read and modify existing ingestion code.
• Comfort with ambiguity and incomplete requirements, with the judgment to know when to ask and when to propose.
• Clear written communication in English.

PREFERRED

• Contact center, BPO, or workforce management metrics: handle time, CSAT, QA, FCR, SLA, adherence, occupancy, and agent-level WFM measures.
• Slowly changing dimensions, particularly for employee or roster data where role changes, transfers, and terminations have to be reconstructable as of a past date.
• Ingestion from imperfect sources such as spreadsheets, shared drives, and manual trackers.
• Snowflake specifically, including an awareness of what drives warehouse cost.
• Multi-client or multi-tenant modeling, where one set of logic serves clients with different source systems and different definitions of the same metric.
• Reporting that carries financial consequence, such as compensation, incentive, or billing calculations.
• Experience working in a layered or medallion-style warehouse architecture.
• Experience supporting analysts or business users as consumers of models, rather than only other engineers.



AVAILABILITY

• Full-time, remote, with overlap required across North America and Asia-Pacific business hours. This is a full-time contractor role.

SKILLS

• Data Modeling and Dimensional Design
• dbt (Models, Tests, Contracts, Versioning)
• Advanced SQL
• Git and Pull-Request Review
• Python (Reading and Modifying Ingestion Code)
• Analytical and Strategic Thinking
• Root Cause Analysis
• Documentation and Runbook Writing
• Stakeholder and Analyst Communication
• Agile/Scrum Sprint Delivery
• Adaptability