Data Architect - Big Data & Analytics

Position: Data Architect - Big Data & Analytics

Location: Onsite- Toronto, ON

Job type: Full-time/Permanent hiring

Job Description

We are seeking a visionary Enterprise Data Architect with over 14 years of experience to lead the architecture, optimization, and long-term modernization of our global Big Data platforms. In this high-impact role, you will own the end-to-end design of large-scale distributed architectures supporting analytics, reporting, and AI workloads. You will serve as the premier technical authority driving cluster optimization, ironclad security governance, and the strategic migration path toward next-generation data platforms.

Key Responsibilities

• End-to-End Platform Architecture: Define the technical blueprint for enterprise-scale Hadoop ecosystems using HDFS, YARN, Spark, Kafka, and Hive.
• Modernization & Migration Planning: Architect migration blueprints, High-Level Designs (HLD), and Low-Level Designs (LLD) to transition legacy data estates into modernized, cloud-ready configurations.
• Data Lake & Streaming Governance: Design structured data lake zones, data models, real-time streaming architectures (Kafka), and automated ETL/ELT pipelines with robust metadata lineage.
• Security & Regulatory Compliance: Implement rigorous enterprise security layers, handling authentication, encryption, auditability, and access control frameworks (Kerberos, Apache Ranger) tailored for highly regulated domains (BFSI).
• Technical Governance & Solutioning: Conduct comprehensive architecture reviews, direct capacity planning, drive performance tuning, support RFP responses, and establish engineering best practices.

Required Technical Skill Set

• Hadoop Core: Expert-level understanding of Hadoop platform internals (HDFS storage, YARN resource allocation, High Availability, and MapReduce).
• Distributed Computing Engine: Advanced hands-on mastery of Spark, PySpark, Hive, and HBase utilizing Python, Java, or Scala.
• Streaming Architecture: Enterprise deployment experience with Kafka for real-time ingestion pipelines.
• Security Governance Frameworks: Complete implementation familiarity with Kerberos and Apache Ranger.
• Enterprise Frameworks: Proven background building reusable data frameworks, managing DataOps, ensuring metadata tracking, and maintaining strict regulatory resilience.