System Architect, Enterprise Platform
Baylor Genetics - Houston, Texas, United States, 77246
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System Architect, Enterprise Platform
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System Architect, Enterprise Platform
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We are seeking an Enterprise Platform System Architect to oversee the architecture of enterprise applications, focusing on ETL processes for the order-to-cash workflow, data warehouse and data lake creation, and overall data management across systems. This role is critical in ensuring the seamless flow, storage, and accessibility of data across enterprise platforms while optimizing performance, security, and scalability. Summary
We are seeking an Enterprise Platform System Architect to oversee the architecture of enterprise applications, focusing on ETL processes for the order-to-cash workflow, data warehouse and data lake creation, and overall data management across systems. This role is critical in ensuring the seamless flow, storage, and accessibility of data across enterprise platforms while optimizing performance, security, and scalability.
The ideal candidate will have deep expertise in enterprise data architecture, ETL processes, data warehousing, and cloud-based platforms. You will work closely with engineering, DevOps, business intelligence, and IT teams to design scalable, efficient, and secure enterprise data solutions.
Responsibilities
Enterprise Architecture & Data Strategy Design and oversee the architecture of enterprise data applications, including ETL pipelines, data warehouses, and data lakes. Define best practices for data governance, security, and compliance across enterprise platforms. Develop strategies to optimize data storage, retrieval, and transformation to support business intelligence and analytics. Evaluate and implement new technologies to improve system efficiency and scalability.
ETL & Data Processing Management Lead the design and implementation of ETL workflows to support the order-to-cash process and other business operations. Ensure data integrity, accuracy, and consistency across multiple enterprise systems. Optimize ETL pipelines for performance, reliability, and scalability. Work with engineering teams to integrate ETL processes with enterprise applications and databases. Data Warehouse & Data Lake Development Architect and manage enterprise data warehouses and data lakes to support analytical and operational needs. Ensure data models are aligned with business requirements and reporting needs. Implement best practices for data ingestion, transformation, and storage. Collaborate with business intelligence teams to facilitate seamless data access for reporting and analytics. Cross-Team Collaboration & Stakeholder Management Partner with software development, DevOps, business intelligence, and IT operations teams to ensure data strategies align with business objectives. Act as a technical advisor for enterprise data initiatives and collaborate with stakeholders to define requirements and solutions. Provide guidance on data architecture decisions, ensuring alignment with industry best practices. Work with leadership to drive enterprise-wide data modernization initiatives. Performance Optimization & Security Compliance Implement strategies to optimize data processing and reduce latency in enterprise applications. Ensure compliance with industry regulations, security standards, and internal policies. Define and enforce data access controls and security best practices. Conduct regular audits and performance assessments to improve system resilience and efficiency. Qualifications 10+ years of experience in enterprise architecture, data engineering, or related fields. Strong expertise in ETL processes, data warehousing, and data lake architecture. Proficiency in SQL, NoSQL, and cloud-based database technologies (AWS, Azure, or GCP). Experience with big data processing frameworks (Spark, Hadoop) and data integration tools. Knowledge of CI/CD pipelines, infrastructure as code (Terraform, Ansible), and DevOps best practices. Strong background in data modeling, governance, and compliance frameworks. Excellent problem-solving, communication, and leadership skills.
Preferred Qualifications Experience with real-time data streaming technologies (Kafka, Kinesis, etc.). Expertise in machine learning data pipelines and AI-driven analytics. Knowledge of microservices architecture and API-driven data integration. Familiarity with ERP, CRM, and financial systems integration.
Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
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