Job Description: Senior Data Engineer (Snowflake, DBT, Fivetran)
Hybrid in Dallas
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 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 dbtdeployments.
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.
