Sr. Data Engineer - PH

Role overview Build trusted data platforms that turn client source systems into reliable business metrics and datasets for analytics and AI. This is a hands-on senior individual contributor role, combining pipeline and model development with discovery alongside client operators, controllers, and analysts.

Responsibilities - Ingest data from databases, APIs, and files, then verify warehouse loads against source-system counts and values. - Operate pipelines across client projects, investigating data freshness, failures, incidents, and infrastructure costs. - Build isolated dbt projects with staging, intermediate, and reporting layers, including fact and baseline models that reconcile to clients’ source-of-truth figures. - Document reconciliation results and translate business discovery into metric definitions and queryable data marts. - Define business rules and tests for metrics, dashboards, and natural-language querying; monitor quality, anomalies, freshness, and sensitive data. - Keep work version controlled, tested, reviewed, and reproducible, and help colleagues develop their data engineering practices.

Requirements - Senior-level data engineering capability and a strong analytical approach to understanding business data. - Ability to build and operate ELT pipelines and layered dbt models. - Skill in validating warehouse data against original systems and explaining discrepancies clearly. - Ability to work directly with client teams to uncover domain logic and turn it into precise metrics. - Judgment to apply sound engineering practices while keeping solutions appropriately scoped.

Nice to have - Experience with semantic layers such as Cube.dev, AI-ready datasets, or structured operational traces. - Familiarity with PII-aware data quality practices and collaborating with platform engineering.