Data Engineer
📍 Location: Irving, TX, United States
🏢 Industry: Hospital and healthcare
💼 Work Setting: Hybrid

Are you passionate about building scalable data platforms, engineering high-performance data pipelines, and transforming complex data into reliable business insights?
Join a technology-driven organization where you'll play a key role in designing, developing, and optimizing enterprise data solutions. As a Data Engineer, you will lead the development of robust data platforms, drive data architecture decisions, and ensure the delivery of high-quality, reliable, and scalable data products that support analytics and business operations.

Key Responsibilities
Data Pipeline & Platform Engineering
Design, develop, and maintain scalable, high-performance data pipelines and modern data platforms.
Build end-to-end data solutions covering data ingestion, transformation, modeling, storage, and consumption layers.
Ensure data platforms support growing business demands while maintaining performance, reliability, and scalability.
Data Architecture & Solution Design
Analyze business and technical requirements to create efficient and scalable data architectures.
Design data workflows and integration patterns that support analytics, reporting, and operational needs.
Define data contracts, service-level expectations, and delivery standards across systems and stakeholders.
ETL/ELT Development & Optimization
Lead the implementation of complex ETL and ELT processes for large-scale data environments.
Optimize data workflows for performance, cost efficiency, reliability, and maintainability.
Improve processing efficiency through automation, monitoring, and advanced engineering practices.
Data Lake & Modern Data Management
Develop and manage modern data lake architectures and associated data processing frameworks.
Implement advanced data management capabilities including schema management, versioning, governance, and optimization techniques.
Support structured and unstructured data processing across enterprise platforms.
Data Quality, Governance & Security
Enforce data governance, security, and compliance standards across data platforms.
Implement access controls, metadata management, cataloging, and data quality frameworks.
Ensure data integrity, accuracy, and consistency across the data lifecycle.
Troubleshooting & Operational Excellence
Investigate and resolve complex data processing challenges, performance bottlenecks, and integration issues.
Diagnose problems involving large-scale distributed systems, data latency, and upstream source changes.
Proactively improve observability, monitoring, logging, and operational support processes.
Collaboration & Technical Leadership
Partner with Product Managers, QA teams, business stakeholders, and engineering teams to deliver reliable data solutions.
Participate in architecture reviews, code reviews, and technical design discussions.
Establish best practices for data engineering, deployment, testing, and operational support.
Mentorship & Knowledge Sharing
Guide and mentor junior engineers on data engineering principles and best practices.
Promote technical excellence through documentation, training, and collaborative problem-solving.
Contribute to continuous improvement initiatives across the engineering organization.

Required Qualifications
Bachelor's degree in Computer Science, Computer Engineering, Information Technology, Data Engineering, or a related field.
5+ years of experience in Data Engineering, Software Engineering, Data Platform Development, or a related role.
Strong experience developing scalable data pipelines and enterprise data solutions.
Proficiency in SQL for data analysis, troubleshooting, and performance optimization.
Experience with Java and Python for application and data pipeline development.
Strong knowledge of relational databases and data management systems.
Experience working with cloud-based storage and data processing platforms.
Familiarity with source code management and collaborative development practices.
Experience integrating systems through APIs and data services.
Knowledge of test automation, software quality assurance, and deployment methodologies.

Preferred Qualifications
Expertise in modern cloud data platforms and distributed data processing environments.
Experience building enterprise-scale analytics and reporting solutions.
Strong understanding of data modeling, data warehousing, and lakehouse architectures.
Experience implementing data governance, metadata management, and security controls.
Knowledge of orchestration tools, workflow automation, and pipeline monitoring frameworks.
Familiarity with Agile software development and DevOps practices.
Strong analytical and problem-solving skills with the ability to resolve complex technical challenges.
Excellent communication and collaboration skills across technical and non-technical stakeholders.
Proven experience mentoring engineers and contributing to technical leadership initiatives.

What You'll Gain
Opportunity to build and scale modern enterprise data platforms that support critical business operations and analytics.
Exposure to cloud-native architectures, distributed processing frameworks, and advanced data engineering technologies.
Collaboration with cross-functional teams across product, engineering, analytics, and business functions.
Professional growth through challenging technical projects, innovation initiatives, and leadership opportunities.
The ability to make a significant impact on data strategy, operational efficiency, and business decision-making.

Data Engineer

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