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# Sr. Data Engineer

- **Company:** CitiusTech
- **Location:** Portland, OR, United States (Remote available)
- **Experience:** Expert
- **Salary:** $120,000.0 - $135,000.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Adaptable Database Systems, Data Governance, Data Profiling, Python (Programming Language), SQL Databases, Strategies of Testing, Snowflake, Data Lineage
- **Published:** July 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=348d22176484b939

## About the Role

* Engineering Degree - BE/ME/BTech/MTech/BSc/MSc.
 * Technical certification in multiple technologies is desirable.

Skills: -

Mandatory skills

 * SQL: Highly Skilled. Must be familiar with common table elements (CTEs), complex joins, and analytic & windowing functions.
 * Python: experience is required.
 * Snowflake: Prefer candidates with real-world experience using Snowflake.
 * Data Profiling: Must be able to identify unique and primary keys and determine cardinality, data type, precision, and scale, and skew.

## Description

* Design and implement scalable data models and pipelines that align with business objectives
 * Develop complex DBT models using advanced features (macros, packages, custom materializations).
 * Collaborate with business leaders to translate complex requirements into technical solutions.
 * Identify and resolve performance bottlenecks in Snowflake queries and DBT models.
 * Optimize Snowflake warehouse configurations and query performance.
 * Design and implement data quality frameworks and testing strategies.
 * Create reusable DBT packages and macros for team-wide use.
 * Manage CI/CD pipelines for DBT deployments.
 * Review and approve pull requests from junior team members.
 * Troubleshoot production issues and implement long-term solutions.
 * Document architectural decisions and data lineage


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- [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases)
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