Build, enhance, and maintain scalable data pipelines using Azure Data Factory
Develop, test, and optimize dbt models for Snowflake and Azurebased lakehouse workloads
Engineer ingestion, transformation, and orchestration workflows across Azure Data Lake Storage
Implement best practices for Snowflake performance tuning, cost optimization, and data modeling
Integrate SQL Server data sources and collaborate with DBAs on operational data flows
Write highquality SQL, Python, and PowerShell to automate and improve data workflows
Monitor pipeline performance, troubleshoot issues, and ensure data reliability and SLA adherence
Partner with business teams to translate data requirements into robust engineering solutions
Contribute to data governance, documentation, and metadata management initiatives
Participate in code reviews and help establish engineering standards and reusable patterns

This candidate should have a BS in computer science, information technology or related technical/engineering field.
3+ years of professional experience in data engineering or a related field
Strong expertise with Azure Data Factory (pipelines, triggers, integration runtimes) and other
Handson experience with Snowflake (warehousing, Snowpipe, RBAC, performance tuning)
Proficiency with dbt (models, tests, macros, documentation)
Advanced SQL skills and experience working with large, complex datasets
Experience with Azure Data Lake Storage and modern Data Lakehouse architecture
Scripting experience with Python and/or PowerShell
Solid understanding of ETL/ELT patterns, data modeling, and CI/CD workflows

Comprehensive and competitive benefits package and flexibility that promotes work-life balance
A work environment where all employees are valued, respected and safe
Freedom to succeed by enabling team members to deliver, take initiatives and make decisions
Recognition, professional development, advancement and having fun!

Data Engineer

Key skills