Data Engineer (Snowflake/dbt)

Location: United States; Remote

Company

hirify.global provides enterprise technology services and operates shared-services information technology capabilities.

What you will do

• Build and operate batch and low-latency ingestion pipelines from enterprise applications, APIs, and approved data sources.
• Develop SQL and Python solutions for collecting, validating, transforming, and publishing data.
• Use Snowflake and dbt to create reliable transformations, reusable models, curated datasets, and data products.
• Apply data-quality checks, metadata, documentation, lineage, ownership, and usage guidance to enterprise data products.
• Implement governed access controls, including role-based access, classification tags, masking, and row- or column-level controls.
• Monitor pipeline health, troubleshoot failures, optimize Snowflake workloads, and participate in Agile delivery, code review, testing, and incident resolution.

Requirements

• Bachelor’s degree in computer science, information systems, engineering, mathematics, or a related field, or equivalent experience.
• 3 or more years of experience in data engineering, software engineering, analytics engineering, or a related technical role.
• Production-quality SQL and Python experience, including data pipelines, transformations, and data models in a cloud environment.
• Experience with Snowflake, dbt, or comparable cloud data warehouse and transformation technologies.
• Understanding of data modeling, ELT/ETL, orchestration, APIs, source-system integration, data quality, metadata, lineage, access control, and data privacy.
• Active use of AI-assisted software development tools and the ability to follow an AI SDLC are required.

Nice to have

• Experience with Azure, serverless functions, cloud storage, REST or GraphQL APIs, and enterprise applications such as Salesforce, Hatch, or NetSuite.
• Familiarity with event-driven processing, observability, data catalogs, lineage tools, and data-quality platforms.
• Experience with semantic models, MCP-based access, master data, entity resolution, and governed interfaces for analytics, automation, or AI workflows.
• Experience using AI agents or agentic workflows for software delivery, data engineering, testing, documentation, or platform operations.

Culture & Benefits

• Product-oriented engineering work under the Director, Data Platform and alongside the Data Governance Lead.
• Collaboration with analytics, application, AI, integration-platform, governance, security, and business teams.
• Iterative delivery within an Agile engineering team.
• Primarily office and computer-based work with regular, punctual attendance expectations.