Sr Data Engineer

Description

We are looking for a Senior Data Engineer to help shape and expand a modern enterprise data ecosystem in Dallas, Texas. This role is ideal for a highly technical specialist who enjoys building scalable cloud-based data solutions, improving platform performance, and collaborating with both engineering and business leaders. The position offers the opportunity to contribute directly to lakehouse design, advanced pipeline development, and data initiatives that support analytics and emerging AI use cases.

Responsibilities:
Architect and develop scalable data platforms using Azure Databricks, Spark, PySpark, Python, Delta Lake, and related big data technologies.
Create and maintain layered lakehouse data models across raw, refined, and curated environments to support enterprise reporting and analytics.
Lead the movement of legacy data assets into Azure-based cloud environments as part of broader platform modernization efforts.
Build, enhance, and monitor high-volume ETL and streaming workflows, notebooks, and distributed processing jobs for reliability and efficiency.
Integrate tools such as Azure Synapse Analytics and Azure Data Factory to support end-to-end data ingestion, transformation, and delivery.
Improve performance of large-scale data workloads by tuning Spark jobs, optimizing code, and applying engineering best practices.
Establish and follow modern software delivery standards through source control, Azure DevOps pipelines, CI/CD processes, and deployment automation.
Prepare and structure data for machine learning, generative AI, and MLOps initiatives, including feature creation and production-ready integration.
Work closely with implementation partners, architects, technical teams, business stakeholders, and senior leadership to align solutions with organizational goals.
Contribute hands-on engineering expertise while also helping guide technical design and platform architecture decisions.

Requirements

At least 5 years of hands-on experience in data engineering, data warehousing, enterprise analytics, or closely related technical work.
Strong practical experience with Azure Databricks in production data environments.
Demonstrated success designing and implementing Medallion-style lakehouse architecture.
Advanced skills in Python, PySpark, Apache Spark, ETL development, and large-scale data processing.
Solid background with Azure cloud services, including experience with tools such as Azure Synapse Analytics and Azure Data Factory.
Experience working with Delta Lake, modern data platform design, and data modeling concepts.
Familiarity with Git-based workflows, CI/CD practices, Azure DevOps, and automated release processes.
Effective communication skills with the ability to collaborate across engineering teams, external partners, business stakeholders, and leadership.

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