Data Engineer – Snowflake, dbt & Fivetran
Location: Addison, TX | Hybrid – Tuesday, Wednesday & Friday onsite
Compensation: $140,000–$160,000
Employment: Full-time
Work Authorization: U.S. Citizens and Green Card holders only. No current or future visa sponsorship.
About the Company
A growing, private equity-backed services organization is investing in its data infrastructure to support better decision-making, operational visibility, and long-term growth.
As the business expands, it is bringing together data from multiple operational and financial systems to create a more consistent, trusted view of performance across the organization.
The company is now building a modern enterprise data platform, creating an opportunity for an experienced Data Engineer to help establish the architecture, pipelines, transformations, and data standards that will support its next stage of growth.
About the Role
We’re looking for a Data Engineer to play a central role in building and owning a modern cloud data environment. This is a hands-on opportunity to help implement Snowflake as the enterprise data warehouse, develop dbt transformations, establish reliable ingestion pipelines, and improve data quality across the business.
You’ll join during a major platform implementation, working alongside external specialists to help establish the initial environment before taking ownership of its ongoing development and operation.
The focus is on the backend data platform, but you’ll need to understand the full data journey—from source-system ingestion and transformation through to the reporting and analytics requirements of the business.
This role is suited to someone who enjoys building, solving data integrity challenges, and establishing engineering standards in an environment where the data function is still evolving.
Key Responsibilities
- Help design, implement, and develop the Snowflake enterprise data warehouse.
- Build and maintain scalable data pipelines across operational, financial, and business systems.
- Develop, test, and maintain dbt models and transformations.
- Implement and optimize ingestion processes using Fivetran or comparable tools.
- Establish reliable data structures and transformation practices that improve consistency across departments.
- Develop data catalogs, documentation, and foundational data governance practices.
- Support data architecture decisions, including warehouse design, data modeling, and integration patterns.
- Partner with implementation consultants and transition the environment into long-term internal ownership.
- Connect backend engineering decisions to downstream analytics and reporting requirements.
- Investigate data discrepancies, improve data quality, and establish repeatable validation processes.
- Collaborate with analysts and business stakeholders to understand requirements and translate them into reliable data solutions.
- Help establish engineering standards, processes, and best practices as the data function grows.
- Support the ongoing evolution of the data platform and future AI-related initiatives.
Must Haves
- Approximately 7+ years of experience across Data Engineering, data warehousing, or related data platform roles.
- Strong hands-on Snowflake experience.
- Strong dbt experience, including building and maintaining transformation models.
- Experience designing, building, and maintaining ETL/ELT pipelines.
- Solid understanding of data warehousing, data modeling, and data architecture.
- Experience integrating data from multiple source systems into a centralized analytics environment.
- Experience identifying and resolving data quality and consistency issues.
- Understanding of data governance, documentation, and data cataloging.
- Ability to work across the full backend data lifecycle, from ingestion through transformation and downstream consumption.
- Comfortable working in an evolving environment and helping establish structure rather than relying on fully mature processes.
- Strong communication skills and the ability to work effectively with analysts, technical teams, and business stakeholders.
Nice to Have
- Fivetran experience, particularly building and maintaining ingestion pipelines.
- Experience implementing or significantly modernizing a cloud data warehouse.
- Medallion architecture or layered data modeling experience.
- Experience integrating data with Domo or similar analytics platforms.
- Experience with operational and financial data from multiple business systems.
- Experience working alongside consultants and transitioning a platform into internal ownership.
- Snowflake Cortex AI exposure or an interest in developing AI-enabled data capabilities.
- Experience coaching colleagues or helping establish data engineering best practices.
Why Join?
Build rather than maintain. Help establish a modern data platform and shape how it develops from the outset.
Own the environment. Work alongside implementation specialists before becoming a key internal owner of the platform.
Solve meaningful data challenges. Improve data integrity, connect fragmented systems, and give business teams a more reliable foundation for decision-making.
Influence technical direction. Contribute to architecture, tooling, data modeling, governance, and engineering standards.
Grow with the function. Join a developing data team with opportunities for increased responsibility as the organization expands.
Contribute to future AI initiatives. Help build the trusted data foundation required for emerging AI and advanced analytics capabilities.
This is an opportunity for a well-rounded, hands-on Data Engineer who wants meaningful ownership of a modern Snowflake environment and the chance to help build a data function for the long term.