Description
### **Be yourself, be your best!**
A e\-Core develops digital solutions and strategic initiatives through specific projects, connecting specialized expertise to the needs of each delivery.
For a specific project, we are seeking a **service provider operating as a legal entity (PJ)**, with technical experience compatible with the scope described below, to deliver results-oriented work and previously agreed-upon deliverables.
### **Project Context**
The client is the largest specialty retailer for skiing and snowboarding in Colorado, with over 59 locations across the U.S. Their current data pipeline runs within a third-party managed Snowflake instance; when the pipeline fails, recovery requires opening a support ticket with the vendor. There is no self\-service restart option.
The Data Engineer service provider will be fully responsible for all technical delivery — from pipeline construction through knowledge transfer.
This is a solo-engineer project — all technical delivery is your responsibility: architectural decisions, build quality, and ensuring a smooth, complete handover. Direct coordination with the client’s internal technical team begins on Day 1 — their availability is a real schedule dependency.
### **Scope of Services**
The services provided will include, but not be limited to:
**Phase 1 — Foundation & EL Pipeline (Weeks 1–6)**
* Design and implement the EL pipeline from the ERP provider’s Snowflake Data Share into the client’s own Snowflake instance hosted in Azure East US;
* Configure Snowflake Tasks;
* Build schema contracts in dbt, automated tests (row count, null checks, referential integrity), and an auto\-generated data catalog — applying data quality, not transformation;
* Implement the initial full historical load from the ERP provider’s Snowflake, followed by daily incremental executions — the architecture must support increased frequency (e.g., twice daily or every 8 hours) without requiring re\-architecture;
* Support redirecting non\-ERP feeds (rental system, HR, other integrations) from the ERP provider’s Snowflake to the client’s own Snowflake instance — working alongside the client’s internal team, who will execute the changes.
**Phase 2 — QA, Documentation & Handover (Weeks 5–9)**
* Validate full data quality across all 159 tables — schema fidelity, row counts, accuracy of incremental executions;
* Produce comprehensive operational runbooks: how to monitor the pipeline, restart failed tasks, add new tables, and extend the incremental schedule;
* Conduct structured knowledge transfer (KT) sessions with the client’s internal team — the goal is full independence starting Day 1;
* Support a 30\-day hypercare period — respond to pipeline issues, monitor alerts, and formally conclude engagement.
All activities will be performed with full technical and operational autonomy, respecting the agreed scope, timelines, and acceptance criteria.
### **Professional Profile Aligned with the Project**
This project aligns with professionals possessing the following skills and experience:
* Hands\-on Snowflake experience — having built and operated production pipelines using Snowflake Tasks, dynamic tables, and schema modeling;
* Snowflake specifically on Azure (East US or equivalent) — AWS-only experience does not satisfy this requirement;
* dbt — production experience using dbt for schema contracts, automated testing, and documentation generation (not just transformation);
* Strong understanding of EL/ETL patterns: incremental loading, change data capture (CDC), pipeline scheduling;
* Advanced SQL — advanced Snowflake SQL proficiency; ability to validate data at scale and write efficient incremental queries;
* English — advanced written and spoken English;
* Azure networking knowledge: private endpoints, VNet configuration, and how these integrate with Snowflake;
* Data documentation — experience producing field mapping documentation and operational runbooks that non\-technical stakeholders can follow;
Incremental pipeline design — practical experience designing pipelines that support increased execution frequency (e.g., daily → multiple times per day) without requiring reconstruction.
### **Desirable Differentiators**
The following will be considered advantageous for the service provider:
* Experience in retail, e\-commerce, or ERP data environments (SAP, Oracle Retail, or similar);
* Snowflake Data Share — experience consuming or publishing Snowflake Data Shares;
* Python — for pipeline orchestration or data validation scripts.
### **Engagement Model**
* Work mode: 100% remote
* Engagement type: Legal entity (PJ)
* Service delivery model: Professional services
* Estimated commitment: Full\-time for the project’s 9\-week duration
* Project duration: 9 weeks
This service engagement does not constitute an employment relationship, subordination, habitual performance, or exclusivity, and is governed by a specific agreement between the parties.
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