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We are looking for a Data Engineer to join a long-term contract opportunity based in Austin, Texas. In this role, you will turn high-level data architecture direction into practical engineering solutions that strengthen a warehouse-first approach and improve how data is collected, transformed, governed, and shared. You will work with technical and business partners to build reliable data foundations that support both operational processes and analytics. This position also plays an important part in elevating internal data engineering practices through clear documentation, reusable standards, and hands-on knowledge sharing.
Job Responsibility
Convert architectural guidance into scalable data pipeline designs and warehouse implementation patterns that support consistent delivery
Build and maintain workflows that ingest source data, prepare it for downstream use, and organize it across raw, staging, curated, and consumption layers
Assess integration approaches and recommend when data should move directly between applications versus through the warehouse for better governance and reuse
Create repeatable standards for orchestration, transformation, testing, monitoring, documentation, and support handoff
Develop and support cloud data warehouse solutions using Snowflake, Matillion, DBT, or comparable data engineering tools based on platform needs
Collaborate closely with integration and cross-functional team members to explain technical choices, guide implementation decisions, and strengthen team capability
Produce clear documentation covering data flows, lineage, dependencies, architecture decisions, and operational expectations
Deliver hands-on engineering leadership that enables durable solutions without creating long-term dependency on external support
Requirements
Senior-level experience in data engineering, data architecture, or a closely related discipline
Extensive hands-on background designing and building ETL and ELT solutions in modern cloud data environments
Demonstrated experience working with Snowflake and transformation tooling such as DBT
exposure to Matillion or similar platforms is highly valued
Ability to translate conceptual architecture into practical, maintainable implementation patterns with minimal supervision
Solid understanding of data integration tradeoffs across application-to-application flows, warehouse-centric design, and operational reporting needs
Proven ability to document technical standards, communicate design rationale, and support knowledge transfer to internal teams
Comfortable partnering with architects, BI leaders, integration specialists, and business stakeholders in a collaborative setting