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# Sr. Software Engineer

- **Company:** Yantran Llc
- **Location:** Durham, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Business Intelligence Development, Continuous Integration, Data Validation, Data Governance, Data Transformation, JSON, Performance Tuning, Power BI, SQL Databases, Tableau (Software), Parquet, Delivery Pipeline, Snowflake, Looker Analytics, Software Version Control
- **Published:** November 7, 2026
- **Apply:** https://www.thejobnetwork.com/job/9bf8a34f-3137-49e0-acfa-dbdfccae620c/sr-software-engineer

## About the Role

Experience integrating Snowflake with BI tools such as
Power BI, Tableau, or Looker .
Exposure to cloud platforms like
AWS, Azure, or GCP .
Knowledge of semia €`structured data formats (JSON, Parquet) in Snowflake.
Understanding of ELT architecture and modern data stack concepts.
Experience with cost optimization and performance tuning in Snowflake

## Description

We are seeking a highly skilled
Data / Analytics Engineer
with strong expertise in
Snowflake, dbt, and SQL
to design, build, and maintain scalable, higha €`performing analytical data platforms. The role focuses on transforming raw data into reliable, analyticsa €`ready datasets that support business intelligence, reporting, and advanced analytics use cases.
Key Responsibilities
Design, develop, and optimize data models and transformations using
dbt
following analytics engineering best practices.
Build and manage scalable cloud data warehouse solutions on
Snowflake .
Develop complex, higha €`performance
SQL
queries for data transformation, analysis, and reporting.
Implement data quality checks, testing, and documentation using dbt tests and exposures.
Collaborate with data analysts, BI developers, and business stakeholders to translate requirements into analyticsa €`ready datasets.
Optimize Snowflake performance using clustering, warehouse sizing, caching, and costa €`control techniques.
Manage and maintain data pipelines ensuring reliability, accuracy, and timeliness.
Implement version control, CI/CD, and deployment workflows for dbt models.
Troubleshoot data issues and perform root cause analysis across the data stack.
Ensure adherence to data governance, security, and compliance standards.