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Robert Half is seeking an experienced Data Architect to design and lead scalable, secure, and high-performing enterprise data solutions. This role will focus on building next-generation cloud data platforms, driving adoption of modern analytics technologies, and ensuring alignment with governance and security standards. You’ll serve as a hands-on technical leader, partnering closely with engineering, analytics, and business teams to architect data platforms that enable advanced analytics and AI/ML initiatives. This position blends deep technical expertise with strategic thinking to help unlock the value of data across the organization.
Job Responsibility:
Design and implement end-to-end data architecture for big data and advanced analytics platforms
Architect and build Delta Lake–based lakehouse environments from the ground up, including DLT pipelines, PySpark jobs, workflows, Unity Catalog, and Medallion architecture
Develop scalable data models that meet performance, security, and governance requirements
Configure and optimize clusters, notebooks, and workflows to support ETL/ELT pipelines
Integrate cloud data platforms with supporting services such as data storage, orchestration, secrets management, and analytics tools
Establish and enforce best practices for data governance, security, and cost optimization
Collaborate with data engineers, analysts, and stakeholders to translate business requirements into technical solutions
Provide technical leadership and mentorship to team members
Monitor, troubleshoot, and optimize data pipelines to ensure reliability and efficiency
Ensure compliance with organizational and regulatory standards related to data privacy and security
Create and maintain documentation for architecture, processes, and governance standards
Requirements:
7+ years of experience in data engineering and data modeling, including at least 2 years in an architecture or senior technical leadership role
Proven experience designing enterprise cloud data platforms (Azure)
Hands-on experience with Databricks (or comparable cloud-based data engineering platforms) for building, orchestrating, and optimizing data pipelines
Hands-on experience building lakehouse architectures using Delta Lake, DLT, PySpark, workflows, Unity Catalog, and Medallion patterns
Nice to have:
Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field
Strong understanding of data security principles and best practices
Experience with platform monitoring and performance tuning
Solid knowledge of DevOps and Infrastructure-as-Code practices, including CI/CD pipelines and automated deployments
Strong analytical and problem-solving skills with the ability to resolve complex technical issues
Experience creating clear technical documentation and operating standards
Relevant cloud or data engineering certifications
Excellent organizational and communication skills, with the ability to work independently while managing multiple priorities
Comfortable working in a fast-paced, collaborative environment