Snowflake dbt Developer

Job Description
ABOUT VICTAULIC
Victaulic, headquartered in Easton, Pennsylvania, is the global leader in mechanical pipe joining solutions, delivering advanced technologies and engineering services to address complex piping challenges faced by engineers, site owners and contractors. Since 1919, our innovative solutions have improved construction productivity and reduced risks, ensuring projects are completed safely, on time, and within budget. With over 6,000 employees spanning 50+ locations worldwide, our teams are dedicated to delivering advanced technologies and engineering expertise that address real-world challenges across a wide range of industries. Our sustainable solutions, made from high quality, graded scrap steel, promote circular construction by making piping systems infinitely reconfigured and minimizing environmental impact. Today, our high-quality products are used in more than 140 countries, supporting some of the world's most critical and prestigious structures.
An Industry Leader With a Heart as Big as Its Ambition and Innovation
At Victaulic, we're committed to constructing a better world for and with our people.
Let's Build a Better World Together.
Our commitment to our people is built on four pillars:
We build from within.
We stand behind our people.
We foster an environment for constant learning.
We engineer change for a more stable and sustainable world.
YOUR IMPACT STARTS HERE
We're seeking a skilled Snowflake dbt Developer to join our growing IT team and build the dbt-based data transformations and Snowflake-native data applications that power reporting, integrations, and AI. This role will focus primarily on developing and extending our production dbt project across the medallion architecture, building the semantic models that power BI and AI consumption, and delivering user-facing solutions with Snowflake Streamlit. The ideal candidate is a hands-on developer with deep expertise in dbt and Snowflake, strong data modeling and SQL skills, a working understanding of data warehousing and lakehouse patterns, and experience building data applications for business users.
WHAT YOU'LL BUILD & OWN
dbt Transformation Development (50%)
Develop, test, and maintain dbt models across the silver, gold, and platinum layers of the medallion architecture.
Extend the production dbt project, including migrating remaining legacy transformation logic, such as Qlik Data Integration, into dbt.
Build and maintain semantic-layer models in the consumption layer to support BI, integration, and AI consumers.
Implement incremental models, snapshots, and materialization strategies optimized for Snowflake performance and cost.
Author dbt tests, including generic, singular, and source freshness tests, and enforce layer contracts, naming conventions, and coding standards.
Maintain dbt documentation, lineage, and exposures so downstream consumers can trust and trace data.
Develop reusable macros and packages to standardize transformation patterns across subject areas.
Participate in pull request reviews and follow the team's GitHub branching and release process for the dbt codebase.
Troubleshoot and resolve dbt model failures, data quality issues, and performance bottlenecks.
Partner with BI analysts and business stakeholders to translate reporting requirements into well-structured dbt models.
Snowflake Native Application Development (25%)
Design and develop interactive data applications using Snowflake Streamlit for self-service analytics and operational workflows.
Implement data-driven solutions leveraging Snowflake's native capabilities to enable business user productivity.
Build applications that enable business users to interact with data through intuitive interfaces.
Create reusable application frameworks and component libraries for rapid solution delivery.
Integrate Snowflake Native Apps and third-party marketplace applications to extend platform capabilities.
Develop custom UDFs and stored procedures to support advanced application logic and business rules.
Data Modeling and Platform Implementation (15%)
Implement data models and pipelines that follow established bronze, silver, gold, and platinum medallion architecture standards.
Apply data warehouse, data lake, and lakehouse patterns, including Apache Iceberg and other open table formats, as directed by the data architecture team.
Implement secure data sharing solutions using Snowflake Marketplace and data sharing capabilities.
Process semi-structured data, including JSON, Parquet, and Avro, into well-modeled, consumable structures.
Optimize query performance, clustering, and warehouse usage for dbt workloads and applications.
Contribute recommendations on modeling patterns and platform features to architecture discussions.
AI Support Through Semantic Modeling (10%)
Build and maintain dbt semantic models, metrics, and business definitions that AI applications and agents can consume consistently.
Develop Snowflake semantic views and semantic model definitions that support natural-language querying tools such as Snowflake Cortex Analyst.
Enrich dbt models with descriptions, column-level documentation, synonyms, and metadata that improve AI accuracy and retrieval.
Prepare curated, AI-ready datasets in the consumption layer with clear grain, relationships, and business context.
Collaborate with AI engineering teams to translate AI use-case requirements into semantic and data model changes.
Validate that AI-generated answers align with governed metric definitions and help diagnose data-related accuracy issues.
WHAT YOU BRING
Education and Experience
Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related technical field.
Minimum of 3 years of experience in data engineering, analytics engineering, or data development roles.
At least 2 years of hands-on experience developing and maintaining dbt projects in production.
At least 2 years of hands-on experience with the Snowflake platform, including advanced features.
Proven track record of developing data applications or analytical solutions for business users.
Technical Skills
dbt Development: Production experience with dbt, including model design, Jinja and macros, testing, packages, documentation, and deployment on Snowflake.
Data Modeling: Strong dimensional modeling skills and experience designing layered transformations, including staging, intermediate, and marts.
Semantic Modeling: Experience defining metrics, dimensions, and business logic in a semantic layer for BI and AI consumption.
Snowflake Expertise: Advanced knowledge of Snowflak