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.
