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# Senior Snowflake Developer.

- **Company:** Healthcare Triangle, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Query Performance, Application Programming Interfaces (APIs), Amazon Web Services, Microsoft Azure, Software as a Service, Cloud Computing, Data Governance, Extract Transform Load (ETL), Data Masking, Data Transformation, Data Warehousing, Database Queries, DevOps, Github, JSON, Python (Programming Language), Package Management Systems, Performance Tuning, Query Optimization, Role-Based Access Control, Cloud Services, SQL Stored Procedures, SQL Databases, Talend, Parquet, Data Processing, Freeform SQL, Google Cloud, Cloud Platform System, Macros, Data Ingestion, Informatica Powercenter, Snowflake, Data Build Tool (dbt), Analytic Functions, Change Data Capture, Git, Data Lakes, Gitlab-ci, Semi-structured Data, Debezium, Data Lineage, Qlikview, Star Schema, Apache Kafka, Stream Processing, Data Pipelines, Databricks
- **Published:** November 14, 2026
- **Apply:** https://www.dice.com/job-detail/c65c7cf1-9475-425e-9592-084cd0420d81

## About the Role

We are looking for a Senior Snowflake Developer with strong expertise in dbt (Data Build Tool), Change Data Capture (CDC), and Delta Processing to design, build, and optimize our next-generation data platform. In this role, you will be responsible for building scalable data pipelines, implementing efficient data transformation layers, and managing real-time/near-real-time data streaming architectures. The ideal candidate possesses deep technical knowledge of Snowflake architecture, advanced data modeling using dbt, and efficient patterns for handling incremental data processing., * Snowflake Expertise: Deep understanding of Snowflake architecture (Cloud Services, Virtual Warehouses, Storage), semi-structured data handling (JSON, Parquet), Time Travel, Zero-Copy Cloning, and Snowpark.

 * Advanced dbt: Proven experience with dbt engineering, including complex macro development, incremental model strategies, package management, and performance tuning at scale.
 * CDC & Stream Processing: Hands-on experience capturing real-time or near-real-time source changes using Snowflake Streams & Tasks, Kafka, or log-based CDC tools.
 * Delta Processing & Handling: Strong grasp of delta logic, idempotency, slowly changing dimensions (SCD Type 1/2/4), and transaction handling.
 * Languages: Expert-level SQL proficiency (analytical functions, window functions, query optimization) and solid experience with Python for data processing.
 * Cloud Platforms: Experience working with cloud ecosystems (AWS, Azure, or Google Cloud Platform) and managing external stages.
 * DevOps for Data: Familiarity with Git, CI/CD pipelines (GitHub Actions, GitLab CI) for deploying dbt code and Snowflake schema changes (e.g., using Schemachange or dbt commands)., * Snowflake Certified Data Engineer (or Advanced Certified).
 * Experience migrating legacy ETL workflows (e.g., Informatica, Talend, stored procedures) into Snowflake/dbt.
 * Experience with Iceberg tables or Databricks Delta Lake integration with Snowflake.

## Description

* Data Pipeline & Architecture: Design, develop, and maintain robust, scalable ETL/ELT pipelines within Snowflake using SQL, Python, and modern data stack tools.
 * dbt Transformation Layer: Architect and manage the dbt environment (dbt Core or dbt Cloud). Write modular, highly optimized dbt models, macros, and tests, ensuring clean data lineage and documentation.
 * CDC & Ingestion: Implement and optimize continuous data ingestion and Change Data Capture (CDC) mechanisms from various source systems (Transactional DBs, SaaS APIs) into Snowflake using tools like Snowflake Pipes (Snowpipe), Streams, Tasks, or external replication tools (e.g., Fivetran, Debezium, Qlik).
 * Delta & Incremental Processing: Design efficient Delta processing architectures utilizing dbt incremental models, Snowflake Streams, and merge strategies to process only modified or new data, minimizing compute costs and latency.
 * Performance Tuning: Optimize complex SQL queries, dbt models, clustering keys, and virtual warehouse configurations to ensure optimal query performance and cost-efficiency.
 * Data Governance & Quality: Implement automated data quality checks, data masking, row-level security, and role-based access control (RBAC) within Snowflake.