Job Description: Senior Data Engineer (Snowflake, dbt, Python, AWS)

Location: Raliegh, NC/NY(Onsite)

Role Overview

We are seeking a Senior Data Engineer who is highly hands-on and experienced in building modern, scalable data pipelines and transformation frameworks using Snowflake and dbt. This role focuses on delivering high-quality, production-grade data solutions with strong engineering discipline, leveraging Python, CI/CD, and Git-based development practices.

The ideal candidate brings deep, practical experience in dbt coding and Snowflake engineering, along with a strong sense of ownership, accountability, and the ability to operate independently. Fivetran experience is beneficial, but the primary focus is on dbt and Snowflake expertise.

Key Responsibilities

• Design, build, and maintain scalable ELT pipelines, leveraging Fivetran (or similar tools) for ingestion and dbt for transformation.
• Develop and maintain robust dbt projects, including:
• Modular models (staging, intermediate, marts)
• Reusable macros and Jinja templating
• Snapshots for SCD Type 2 handling
• Schema and custom data quality tests
• Documentation using dbt docs
• Implement modular and reusable dbt architecture supporting multi-environment deployments (dev, test, prod).
• Design and implement scalable data models using best practices (dimensional modeling, star schema, and data vault where applicable).
• Optimize Snowflake performance and cost efficiency, including:
• Query tuning and execution optimization
• Warehouse sizing and workload management
• Effective use of micro-partitions, clustering, and pruning
• Build and enforce strong data quality and validation frameworks, including:
• Unit testing for transformations (dbt and custom frameworks)
• Data reconciliation and consistency checks
• Develop Python-based solutions for automation, orchestration support, metadata-driven processing, and operational tooling.
• Implement and enforce Git-based development practices:
• Version control, branching strategies, pull requests, and code reviews
• Consistent and collaborative engineering workflows
• Build, maintain, and enhance CI/CD pipelines for dbt deployments:
• Automated build, test, and deployment processes
• Environment promotion (dev ? test ? prod)
• Integration with enterprise deployment pipelines
• Work with orchestration tools such as Airflow / Astronomer to schedule, monitor, and manage data pipeline execution (preferred).
• Collaborate closely with platform, governance, and business teams to align on data requirements, access control, and delivery expectations.

Required Qualifications

• 10+ years of experience in data engineering / analytics engineering roles.
• Strong hands-on experience with AWS
• Strong hands-on experience with dbt in production, including:
• Model development and dependency management
• Macro development and reusable frameworks
• Testing strategies (schema tests, custom tests)
• Deployment and environment management
• Strong Snowflake expertise, including:
• Data modeling and warehouse design
• Performance tuning and cost optimization
• Deep understanding of virtual warehouses, micro-partitions, clustering, and query pruning
• Role-based access control (RBAC) and secure data access
• Advanced SQL expertise with ability to build and optimize complex transformations.
• Strong Python programming skills for data engineering use cases.
• Proven experience with Git integration, including collaborative development workflows.
• Strong experience implementing CI/CD pipelines for data platforms and dbt deployments.
• Experience building and maintaining production-grade data pipelines with SLAs, monitoring, and reliability standards.

Preferred Qualifications

• Experience with Fivetran (connector setup, ingestion patterns, schema management, troubleshooting).
• Experience with Airflow / Astronomer or similar orchestration tools.
• Exposure to data governance, lineage, and observability tools.
• Financial services / banking domain experience is strongly preferred and will be prioritized, though not mandatory.