> Markdown version of [/jobs/ext/3212798-data-engineer](https://www.wearedevelopers.com/jobs/ext/3212798-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer

- **Company:** Profocus, Inc.
- **Location:** United States
- **Experience:** Expert
- **Salary:** $124,800.0 - $156,000.0
- **Contract:** Temporary contract
- **Skills:** Databases, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Mapping, Relational Databases, Database Queries, SQL Databases, Data Streaming, Systems Integration, Enterprise Data Management, Enterprise Application Integration, Data Logging, Snowflake, Operational Systems, Data Management, Tools for Reporting, Api Design, Data Pipelines, Legacy Systems
- **Published:** September 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1c9c3bc80f288af5

## About the Role

* 5+ years of hands-on data engineering, data integration, or related engineering experience
 * Strong SQL skills and experience working with complex relational data
 * Production experience with modern cloud data platforms; Snowflake experience strongly preferred
 * Experience designing and maintaining ETL/ELT pipelines
 * Experience working with APIs, files, databases, batch integrations, and other enterprise integration patterns
 * Experience implementing automated data-quality checks and reconciliation processes
 * Experience with pipeline orchestration, monitoring, logging, and failure recovery
 * Strong understanding of data modeling, transformation, and source-to-target mapping
 * Strong documentation and technical communication skills
 * Experience in retail, supply chain, inventory, merchandising, e-commerce, loyalty, or financial data environments is preferred

## Description

This is an experienced Data Engineer position focused on strengthening the reliability, accessibility, and trustworthiness of data across a complex enterprise environment.
You'll provide hands-on engineering expertise to understand, stabilize, and improve how data moves between operational systems, the enterprise data platform, reporting tools, and downstream consumers. This includes tracing data flows and lineage, strengthening ETL/ELT pipelines and integrations, implementing automated data-quality controls, and improving monitoring, alerting, documentation, and failure recovery.
This is not a greenfield environment. You'll work with existing integrations, legacy systems, undocumented dependencies, manual processes, and varying levels of data quality. The goal is to make the current environment more understandable and reliable while establishing sustainable engineering practices that support future modernization.