Data / Analytics Engineer with strong expertise in Snowflake, dbt

American IT Systems
Durham, NC, United States
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Amazon Web Services Data Analysis Microsoft Azure Business Intelligence Development Cloud Computing Continuous Integration Data Validation Data Governance Data Transformation JSON Performance Tuning Power BI
+9 more
SQL Databases Systems Integration Tableau (Software) Parquet Delivery Pipeline Snowflake Caching Looker Analytics Software Version Control

Job description

  • 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, high `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 analytics `ready datasets.
  • Optimize Snowflake performance using clustering, warehouse sizing, caching, and cost `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.

Requirements

We are seeking a highly skilled Data / Analytics Engineer with strong expertise in Snowflake, dbt, and SQL to design, build, and maintain scalable, high performing analytical data platforms. The role focuses on transforming raw data into reliable, analytics ready datasets that support business intelligence, reporting, and advanced analytics use cases., Preferred Qualifications * Experience integrating Snowflake with BI tools such as Power BI, Tableau, or Looker.

  • Exposure to cloud platforms like AWS, Azure, or GCP.
  • Knowledge of semi `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

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