Senior Data Engineer (Azure)

TL;DR

Senior Data Engineer (Azure/Snowflake): Designing and building a cloud-native data lakehouse from raw ingestion to analytics-ready tables with an accent on Medallion architecture and data observability. Focus on developing scalable ETL/ELT pipelines, optimizing Snowflake performance, and implementing automated data validation.

Location: On-site in Miami, FL or Seattle, Washington

Company

hirify.global is a global leader in network security and intelligence, providing advanced endpoint protection and secure Wi-Fi solutions to over 250,000 customers worldwide.

What you will do

• Design and maintain scalable ETL/ELT pipelines using Azure Data Factory and Apache Airflow across a Medallion architecture.
• Build and optimize Snowflake data warehouse objects including tables, views, and stored procedures for performance and cost efficiency.
• Develop modular, tested dbt models and implement data observability using Elementary for anomaly detection and freshness checks.
• Manage Azure Cloud infrastructure including ADLS Gen2, Azure Key Vault, and event-driven processing via Azure Functions and Logic Apps.
• Translate complex business requirements into technical data models and pipeline designs in collaboration with stakeholders.
• Mentor junior engineers and champion CI/CD adoption for pipeline and dbt model deployments.

Requirements

• 4+ years of professional data engineering experience, with at least 2 years on Azure cloud data platforms
• Advanced SQL proficiency and deep expertise in Snowflake native features (streams, tasks, snowpipe, dynamic tables).
• Hands-on experience writing and documenting production dbt models and using Elementary for observability.
• Proficiency in Azure Data Factory, ADLS Gen2, and Azure Key Vault management.
• Strong Python skills for pipeline scripting, PySpark basics, and REST API integration.
• Proven experience implementing Bronze/Silver/Gold Medallion architecture and SCD Type 2 dimension management.

Nice to have

• Exposure to Snowflake Cortex, dbt Semantic Layer, or Boomi Data Hub for AI-assisted data enrichment.
• Experience integrating LLM-based quality checks or AI-assisted anomaly detection into data workflows.
• Familiarity with Microsoft Fabric and OneLake.
• Knowledge of data mesh or data product thinking.
• Experience with Terraform or Bicep for infrastructure provisioning.

Culture & Benefits

• Culture rooted in Accountability, Community, Belonging, Action, Innovation, and Customer-Centricity.
• Commitment to diversity and equal employment opportunities.
• Work within a global leader in the network security domain.
• Standard U.S. corporate benefits package.