Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Engineer position for a long-term contract (3 to 6 months) working remotely in the US (PT hours). Key skills include GCP, Big Query, dbt Core, data modeling, and ETL pipelines.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 17, 2025
🕒 - Project duration
3 to 6 months
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🏝️ - Location type
Remote
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#IP (Internet Protocol) #dbt (data build tool) #GA4 (Google Analytics 4) #GCP (Google Cloud Platform) #Data Modeling #BI (Business Intelligence) #Datasets #Data Engineering #IAM (Identity and Access Management) #Logging #Cloud #Looker #Storage #Data Layers #"ETL (Extract #Transform #Load)"
Role description
Title: Data Engineer
Location: Remote – Anywhere in the US (must work PT hours)
Contract: Long Term Contract
Project Scope (Phases 0–1):
Phase 0 – Foundations (Month 0–1):
• GCP project setup, IAM, and audit logging.
• Object storage (GCS) buckets with Raw → Clean → Gold layers + retention rules.
• Big Query datasets aligned with data layers.
• dbt Core scaffolding (open source, no vendor lock-in).
• Static IP setup for SFTP partner access.
Phase 1 – Early Value (Month 1–2):
• GA4/Firebase native export into Big Query.
• Partner SFTP ingestion → GCS → Big Query.
• dbt models for KPIs (active users, deposits, offers, conversions).
• Insight dashboards with Looker Studio (preferred, not mandatory).
Key Skills:
• Strong experience with Google Cloud Platform (GCP), Big Query, and dbt Core.
• Hands-on expertise in data modeling, ETL pipelines, and orchestration.
• Familiarity with SFTP integrations and secure data transfer.
• Knowledge of Looker Studio or other BI tools is a plus.
Title: Data Engineer
Location: Remote – Anywhere in the US (must work PT hours)
Contract: Long Term Contract
Project Scope (Phases 0–1):
Phase 0 – Foundations (Month 0–1):
• GCP project setup, IAM, and audit logging.
• Object storage (GCS) buckets with Raw → Clean → Gold layers + retention rules.
• Big Query datasets aligned with data layers.
• dbt Core scaffolding (open source, no vendor lock-in).
• Static IP setup for SFTP partner access.
Phase 1 – Early Value (Month 1–2):
• GA4/Firebase native export into Big Query.
• Partner SFTP ingestion → GCS → Big Query.
• dbt models for KPIs (active users, deposits, offers, conversions).
• Insight dashboards with Looker Studio (preferred, not mandatory).
Key Skills:
• Strong experience with Google Cloud Platform (GCP), Big Query, and dbt Core.
• Hands-on expertise in data modeling, ETL pipelines, and orchestration.
• Familiarity with SFTP integrations and secure data transfer.
• Knowledge of Looker Studio or other BI tools is a plus.
