Lead Analytics Engineer

Newport World Resorts; Pasay; On-site; PHP 3,500,000 - 6,200,000; Full time

Job summary

Newport World Resorts is seeking a Lead Analytics Engineer to steer data modelling initiatives across its Casino Marketing, Membership, CX, DPP, and Finance teams. You will define the data model strategy, own the Silver/Gold layers, and drive governance and testing standards across the platform.

You will lead the Analytics and Data Engineering team, delivering sound models, reusable metrics, and robust CI/CD practices while ensuring data quality and cross-property consistency.

Qualifications

• Bachelor's degree in a relevant field.
• 7+ years in analytics/data/BI with data modeling experience.
• Proven ability to translate business questions into data models.
• Experience leading a technical team and setting engineering standards.
• Hands-on with cloud data warehouses and dbt or similar tools.
• Familiarity with Git, CI/CD and governance practices.
• Experience with gaming/hospitality/retail or loyalty data is aPlus.
• Advanced SQL and dimensional modeling skills.
• Knowledge of Snowflake governance and access controls.

Responsibilities

• Be the primary point of contact for data modelling requirements from business teams.
• Design and own Silver and Gold data models across properties.
• Lead dbt standards, code reviews and testing approaches.
• Ensure data quality, lineage and governance across the platform.
• Mentor and manage the Analytics and Data Engineering team.
• Collaborate with platform teams on CI/CD and deployment workflows.

Skills

Leadership

Stakeholder engagement

Advanced SQL

Data modeling

Analytics engineering

Education

Bachelor's degree in CS/IS/Engineering/Math/Stats

Tools

Snowflake

dbt

Python

Job description

JOB SUMMARY

• The Lead Analytics Engineer is the main point of contact for anyone at NWR who needs data modelled. Business teams and Data & Analytics bring their requirements to this role. The Lead Analytics Engineer works out what is really needed, turns it into a sound data model, decides where each part belongs in the platform, and sees it through to delivery.

• The role leads the Analytics and Data Engineering team, with Data Engineers reporting directly to it. It sets the standards the team builds to and leads code review. It is hands‑on: the Lead Analytics Engineer designs and builds models, not only reviews them.

RESPONSIBILITIES

• Modelling requirements: the front door into DP&E

  • Be the entry point into DP&E for data modelling requests from Casino Marketing, Membership, CX, DPP, Finance and Data & Analytics.

  • Work with each requester to pin down the business question, how the data will be used, the level of detail (grain), how much history is needed and how fresh it must be, before any build starts.

  • Check whether an existing model already meets the need before building something new.

  • Turn each request into a short written model design (layer, grain, keys, history approach, tests) and agree it with the requester.

  • Agree priorities for incoming requests with the VP, and be clear with requesters on what is in, what is out and when it will land.

  • Push back when a request would break our design principles, and offer an alternative that still meets the need.

• Data model design

  • Own the design of the Silver and Gold models: grain, keys, shared dimensions, history tracking, and what belongs in each layer.

  • Make sure models work across properties (NWR, Winford and Westside), so customer value can be shown by property and for the group.

  • Turn metric definitions agreed with Data & Analytics into models that calculate each metric once and reuse it everywhere.

  • Keep model documentation and the data dictionary current, with descriptions clear enough for BI and AI tools to use.

• Engineering standards and code review

  • Set and maintain the team's dbt standards: naming, structure, tests and documentation.

  • Lead code review on the dbt repositories and act as the main reviewer for model changes.

  • Own the testing approach, and work with the platform team on CI/CD and the branching flow (feature, qa, main).

  • Apply data governance inside the platform: access roles, masking and row-level rules for sensitive data.

• Delivery and data quality

  • Build and maintain models hands‑on, especially the most complex or cross‑domain ones.

  • Set data quality and freshness checks on key datasets and act on failures.

  • Trace data issues back to source with the engineers and source system owners.

• People leadership

  • Manage the Data Engineers: set goals, review performance and give regular feedback.

  • Coach the team on modelling, SQL performance and good practice, with a development plan for each person.

  • Hire into the team.

  • Keep the team engaged and the workload balanced.

  • Stand in for the VP on technical decisions when needed.

QUALIFICATIONS

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics or a related field

• 7 or more years in analytics engineering, data engineering or BI development, including at least 3 years designing dimensional models for a data warehouse.

• Has gathered requirements directly from business users and turned them into model designs that were built and used.

• Has led code review or set engineering standards for a team.

• Has managed or led a team of engineers, including setting goals and giving feedback.

• Hands‑on with a cloud data warehouse (Snowflake preferred; BigQuery, Redshift, Databricks or Synapse considered) and with dbt or a similar transformation tool.

• Works in Git with CI/CD.

• Experience with gaming, hospitality, retail or loyalty data is an advantage.

• Advanced SQL, including performance tuning.

• Dimensional modelling: grain, shared dimensions, slowly changing dimensions, facts at the right level of detail.

• dbt: models, tests, macros, documentation and incremental builds.

• Data quality testing and monitoring.

• Snowflake access control and governance (roles, masking, row access). Python is useful.

• Snowflake and/or dbt certifications are an advantage