Data Platform Architect

About the role

We are seeking an experienced Data Platform Architect to lead the strategic modernization of our enterprise data ecosystem. This role will be responsible for defining and executing the architecture for large-scale data platform transformations, utilizing technologies both on-premise and in the cloud. The ideal candidate will collaborate across engineering, infrastructure, architecture, and business teams to establish the future-state data platform strategy.

Responsibilities

• Define the target-state architecture for enterprise data platforms and cloud-native analytics solutions.
• Lead the migration of large-scale data environments from on-premises platforms to a cloud environment.
• Design scalable, resilient, and secure data architectures capable of supporting petabyte-scale workloads.
• Establish architectural standards, governance frameworks, and engineering best practices.
• Partner with infrastructure, security, and application teams to ensure alignment with enterprise cloud strategies.
• Evaluate and recommend technologies for data storage, processing, streaming, governance, and observability.
• Provide technical leadership and mentorship to engineering teams implementing Spark, Kafka, Databricks, and cloud-native services.
• Drive performance optimization, cost management, and operational excellence across the data platform.
• Support executive stakeholders with migration roadmaps, risk assessments, and modernization strategies.

Requirements

• 10+ years of experience in data platform architecture, data engineering, or distributed systems.
• Demonstrated experience leading enterprise-scale cloud migration initiatives involving hundreds of terabytes or petabytes of data.
• Experience migrating data from platforms such as Vertica, Hadoop, Teradata, Oracle, Snowflake, or similar technologies.
• Experience designing highly available, scalable distributed systems.

Skills

• Strong experience with Databricks, Apache Spark, Apache Kafka, AWS cloud services, and large-scale data warehouse or lakehouse platforms.
• Experience with AMPS, MQ, Hadoop, or other enterprise messaging systems.
• Strong software engineering background with expertise in Java, Python, SQL,