Data Platform Architect

About the role We are seeking a highly experienced Data Platform Architect to lead the design, development, and optimization of enterprise-scale data platforms and modern analytics ecosystems. This role will be responsible for architecting cloud-native data solutions, designing scalable data pipelines, enabling AI-driven analytics, and establishing best practices across data engineering, integration, and platform governance. Key responsibilities Design and architect scalable, cloud-native data platforms and modern analytics solutions Lead the development of enterprise data pipelines, ingestion frameworks, and lakehouse architectures Define data architecture standards, best practices, and technology roadmaps Design and optimize ETL/ELT frameworks supporting large-scale data processing workloads Collaborate with business stakeholders, architects, data scientists, and engineering teams to deliver data-driven solutions Drive data platform modernization, automation, and cloud migration initiatives Architect and support distributed data processing environments using Spark-based technologies Establish governance, performance, scalability, security, and operational standards across the data ecosystem Provide technical leadership, mentoring, and architectural oversight to data engineering teams Evaluate and recommend emerging technologies to support enterprise data and AI initiatives About you Bachelor's Degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related discipline 8+ years of overall experience in Data Engineering, Data Platforms, Big Data, Analytics, or Data Architecture 6+ years of hands-on experience designing and delivering enterprise data solutions Strong experience with Snowflake and cloud-based data platforms Hands-on expertise in Spark, Apache Spark, and PySpark Experience designing and supporting modern ETL/ELT frameworks Knowledge of GBI ETL Frameworks and enterprise data integration practices Strong experience with Apache Airflow for workflow orchestration and automation Experience with Apache Kafka and event-driven data architectures Hands-on experience with Apache Iceberg and modern lakehouse architectures