Senior Data Engineer (Contract) – Build BigQuery Warehouse & ETL (LATAM Preferred)
Scope of Work – Project-Based Data Engineer (LATAM Preferred)
Project Overview
Forward Storage is seeking a contract-based Data Engineer to design, implement, and document a modern data warehouse and ETL/ELT architecture. The goal is to centralize operational, financial, sales, and marketing data into an analytics-ready warehouse to support Tableau/Power BI reporting.
This engagement is project-based with a clearly defined build phase, followed by optional light ongoing support.
Primary Objectives:
- Design and implement a scalable, low-maintenance data warehouse.
- Establish automated data pipelines from core SaaS platforms.
- Model data into analytics-ready fact and dimension tables.
- Ensure data accuracy, reliability, and documentation for long-term ownership by the internal analyst.
Initial Data Sources:
- Cubby – property management (financial & operational data)
- AppFolio – property management (financial & operational data)
- HubSpot – CRM, leads, sales funnel data
- Google Ads – campaign, spend, performance data
- Facebook Ads – campaign, spend, performance data
Preferred Technology Stack (Open to Vetting):
- Data Warehouse: Google BigQuery (preferred), Snowflake or equivalent acceptable
- ELT / Ingestion: Airbyte (preferred), Fivetran, Stitch, or equivalent
- Transformation Layer: dbt (Core or Cloud preferred)
- BI Tool: Tableau (preferred), others to be considered
- Version Control: GitHub or GitLab
Note: The engineer may recommend alternative tools if they better meet reliability, cost, or maintainability goals. Final stack selection will be mutually agreed upon.
Scope of Work
Phase 1 – Discovery & Architecture (1–2 weeks)
- Review available APIs, data schemas, and access methods for all source systems
- Recommend final warehouse and ELT architecture
- Define data ingestion strategy (incremental loads, refresh cadence)
- Establish naming conventions, schemas, and data modeling standards
- Define high-level data governance and quality approach
Phase 2 – Implementation & Modeling (3–5 weeks)
- Configure cloud data warehouse environment
- Build automated ELT pipelines for all Phase 1 data sources
- Create raw/staging tables with minimal transformation
- Develop transformed models including:
o Financial metrics by property and time
o Operational performance (occupancy, units, activity)
o Sales and funnel metrics from HubSpot
o Marketing spend and performance by channel
- Design analytics-ready fact and dimension tables
- Implement incremental refresh logic and basic data validation tests
Phase 3 – QA, Documentation & Handoff (1–2 weeks)
- Validate data accuracy with the internal analyst and stakeholders
- Optimize queries and model performance
- Deliver documentation including:
o Data dictionary
o Entity-relationship overview
o Pipeline refresh schedule
- Walkthrough and handoff to internal analyst
- Finalize Git repository and project artifacts
Out of Scope
- Advanced ML or predictive modeling
- Real-time streaming architecture (unless separately agreed)
- Ongoing dashboard development
- Long-term infrastructure monitoring beyond agreed retainer
Deliverables
- Production-ready data warehouse
- Automated ELT pipelines
- Analytics-ready data models
- Documentation and handoff materials
- Optional support transition plan
Timeline
- Estimated total duration: 6–8 weeks
Compensation & Engagement Model
- Fixed project budget: USD TBD
- Milestone-based payments preferred
- Optional ongoing support retainer: 5–10 hrs/month
Required Qualifications
- 5+ years of data engineering or analytics engineering experience
- Strong SQL and data modeling skills
- Experience with cloud data warehouses (BigQuery, Snowflake, etc.)
- Experience with ELT tools (Airbyte, Fivetran, dbt, etc.)
- Familiarity with SaaS data sources (CRM, Ads platforms, financial systems)
- Comfortable working independently in a remote environment
- Clear written and spoken English
Success Criteria
- Reliable, automated data refreshes
- Clean, documented, analytics-ready data models
- Minimal ongoing engineering dependency
- Smooth handoff to internal analyst
Apply Now
Apply Now