Data Platform Architect - AIRLKLHV

NavitasPartners • Los Angeles, CA

7h • Hybrid

About The Position

We are seeking an experienced Data Platform Architect to design and implement scalable, high-performance data platforms that support enterprise analytics, machine learning, and reporting initiatives. This role is critical in building the data foundation that enables data-driven decision-making across the organization. The ideal candidate will bring deep expertise in modern data architectures, including lakehouse models and cloud-based ecosystems, along with the ability to align technical solutions with business objectives.

Requirements

• Extensive experience designing and implementing modern data architectures
• Strong knowledge of cloud data platforms (AWS, Azure, or GCP)
• Hands-on experience with ETL/ELT tools and data pipeline development
• Solid understanding of data governance, security, and compliance practices
• Experience working in large-scale enterprise data environments
• Strong expertise in database technologies and data modeling
• Ability to translate complex business requirements into scalable technical solutions
• Proven experience designing enterprise-scale data platforms supporting AI/ML workloads
• Experience integrating legacy systems with modern cloud data platforms
• Strong problem-solving, architecture, and decision-making skills
• Excellent communication and collaboration abilities

Nice To Haves

• Experience with lakehouse architectures (e.g., Delta Lake, Iceberg, or similar)
• Familiarity with big data processing frameworks (e.g., Spark)
• Knowledge of data observability and monitoring tools
• Experience with MLOps and data platform optimization for AI use cases

Responsibilities

• Design and implement enterprise-grade data platforms for large-scale analytics and AI use cases
• Develop and optimize data pipelines for ingestion, transformation, and storage (ETL/ELT)
• Evaluate and recommend data technologies based on business and technical requirements
• Define and implement data governance, security, and compliance frameworks
• Collaborate with cross-functional engineering teams to integrate data systems seamlessly
• Optimize data infrastructure for performance, scalability, and reliability
• Enable advanced analytics and machine learning workloads
• Provide technical leadership, guidance, and mentorship to data engineering teams

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 1-10 employees