Role Overview

We are seeking a Senior Analytics Engineer / Data Warehouse Lead to design, build, and own the company's centralized Data Warehouse.

The primary responsibility of this role is to establish a scalable, reliable, and business-ready data foundation consolidating data from SCALE PMS, ERP, HubSpot, Google Ads, Meta Ads, and Finance systems.

The role will lead the Data Warehouse initiative end-to-end, coordinating with external architects or specialized consultants when required, while retaining full ownership of data models, business logic, and analytical outcomes..

Key Responsibilities

Own and drive the end-to-end design and implementation of the Data Warehouse, including architecture, modeling, and data flow design.
Consolidate data from multiple internal and external systems (PMS, ERP, CRM, Ads, Finance) into a single, trusted data platform.
Design and maintain data models and transformations (Bronze / Silver / Gold layers) to produce accurate, consistent, and analytics-ready datasets.
Build, manage, and optimize data pipelines (ETL/ELT), including source mapping, cleansing, validation, and automated refresh processes.
Define and enforce data quality standards, validation rules, and governance, ensuring reliability and transparency of business metrics.
Establish and maintain company-wide KPIs, metric definitions, and analytical logic as a single source of truth.
Create, maintain, and support dashboards and analytical outputs as needed to validate data models and support management decision-making.
Own marketing attribution logic across advertising, CRM, and operational systems (Ads HubSpot PMS ERP).
Perform deep-dive and ad-hoc analyses to identify trends, inefficiencies, and optimization opportunities across revenue, costs, and operations.
Collaborate with external data architects, engineers, or consultants hired on a project basis, while retaining ownership of overall data outcomes.
Proactively identify opportunities to improve data architecture, automation, and analytical processes beyond the initial implementation scope.

Qualifications

Bachelor's or Master's degree in Data Analytics, Computer Science, Engineering, or a related field.
Minimum 5 years of experience in analytics engineering, data engineering, or data warehouse-focused roles.
Strong expertise in SQL, dbt, Python, and data warehouse design (e.g. BigQuery, Snowflake, Postgres, or similar).
Proven experience building and owning Data Warehouses across multiple data sources.
Solid experience with BI and visualization tools (Power BI, Looker Studio, Metabase, or equivalent).
Demonstrated ability to integrate ERP, PMS, CRM, and marketing platforms into a unified analytics layer.
Strong analytical thinking, ownership mindset, and ability to work cross-functionally with technical and non-technical stakeholders.