Data Engineer

Description

We are looking for a Data Engineer to join our team in Texas. In this role, you will create and enhance modern cloud data platforms that power reporting, analytics, and intelligent business solutions. The position is ideal for a hands-on individual who excels at building scalable pipelines, improving data performance, and partnering with technical and business teams to deliver reliable data products.

Responsibilities

Create and maintain cloud-based data solutions on Azure using services such as Databricks, Synapse Analytics, Data Factory, and related platform tools. Build resilient data pipelines and integration workflows that support enterprise analytics, reporting, and business intelligence across large and complex datasets. Architect and implement lakehouse and warehouse environments, including layered data models that organize raw, refined, and business-ready data.

Develop reusable notebooks and processing frameworks with Python, PySpark, Spark, and Scala to support scalable engineering patterns. Tune and troubleshoot data workloads to improve speed, stability, scalability, and overall cost efficiency in production environments. Deliver end-to-end data solutions by handling design, development, testing, deployment, documentation, and ongoing operational support. Apply source control, DevOps practices, and automated release processes to enable consistent and secure deployments.

Partner with stakeholders, engineers, and leadership to convert business needs into practical technical designs and data solutions. Support AI and machine learning initiatives through data preparation, feature development, curated datasets, and platform capabilities for advanced analytics. Investigate production issues, evaluate new technologies, and recommend improvements that strengthen reliability, efficiency, and business value.

Requirements

At least 7 years of experience in cloud data engineering, data integration, data warehousing, and enterprise analytics environments. Strong practical experience with Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and broader Azure data services. Demonstrated success designing lakehouse solutions and implementing layered data architectures for raw, transformed, and curated data. Advanced coding skills in Python, PySpark, Spark, SQL, T-SQL, and Scala for large-scale data processing.

Proven ability to develop and optimize Databricks notebooks and distributed processing jobs handling high-volume workloads. Experience with Git, Azure DevOps, CI/CD pipelines, and automated deployment practices in cloud-based development environments. Solid understanding of data warehouse design, dimensional modeling, data governance, metadata management, and data quality principles. Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related technical field, or equivalent hands-on experience.

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