Enterprise Data Architect
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- 14+ years of experience in Enterprise Data Architecture, Hadoop Ecosystem, Big Data Engineering, and Data Platform Modernization.
- Posting language
- English
- Posted
Original job description
- 14+ years of experience in Enterprise Data Architecture, Hadoop Ecosystem, Big Data Engineering, and Data Platform Modernization.
- Strong hands-on expertise in Hadoop, HDFS, YARN, Hive, Spark, PySpark, Kafka, SQL, Python, Java, and Scala.
- Experience designing and implementing large-scale Big Data and Data Lake architectures supporting analytics, reporting, and AI workloads.
- Strong understanding of Hadoop platform architecture, including HDFS, YARN, high availability, cluster management, workload optimization, and scalability.
- 14+ years of experience in Enterprise Data Architecture, Hadoop Ecosystem, Big Data Engineering, and Data Platform Modernization.
- Strong hands-on expertise in Hadoop, HDFS, YARN, Hive, Spark, PySpark, Kafka, SQL, Python, Java, and Scala.
- Experience designing and implementing large-scale Big Data and Data Lake architectures supporting analytics, reporting, and AI workloads.
- Strong understanding of Hadoop platform architecture, including HDFS, YARN, high availability, cluster management, workload optimization, and scalability.
- Expertise in batch and distributed data processing using Spark, Hive, HBase, and MapReduce frameworks.
- Experience building data ingestion and streaming solutions using Kafka and Hadoop ecosystem tools.
- Strong knowledge of Data Engineering practices, including ETL/ELT, data integration, data quality, metadata management, lineage, observability, and DataOps.
- Experience with Data Lake, Data Warehousing, Enterprise Data Models, Master Data, and Data Governance frameworks.
- Strong understanding of security and governance controls, including Kerberos, Ranger, encryption, privacy, auditability, compliance, and controlled data access.
- Proven experience in architecture definition, HLD/LLD creation, migration planning, technical governance, production readiness, and performance optimization.
- Experience supporting platform modernization, cloud adoption, solutioning, effort estimation, and client-facing technical discussions.
- Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements.
- Preferred certifications in Hadoop, Spark, Cloud Data Engineering, Enterprise Architecture, Data Management, Security, or Big Data Platforms.
More about this job
Responsibilities
Design and implement large-scale Big Data and Data Lake architectures for analytics, reporting, and AI workloads, while supporting distributed processing, data ingestion, streaming, and platform modernization. Define architecture and technical governance, create HLD/LLD documentation, plan migrations, optimize performance, and ensure production readiness, security, and compliance.
Requirements
Requires 14+ years of experience in Enterprise Data Architecture, Hadoop, Big Data Engineering, and data platform modernization, with hands-on expertise across Hadoop ecosystem technologies, programming languages, and distributed data processing frameworks. Candidates should also have strong knowledge of data engineering, governance, security, architecture delivery, cloud adoption, and BFSI regulatory requirements; relevant certifications are preferred.
Skills
- Enterprise Data Architecture
- Hadoop
- HDFS
- YARN
- Hive
- Spark
- PySpark
- Kafka
- SQL
- Python
- Java
- Scala
- Big Data Engineering
- Data Lake Architecture
- Data Governance
- ETL/ELT
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Engineering
- Consulting
Keywords
- Enterprise Data Architecture
- Hadoop Ecosystem
- Big Data Engineering
- Data Platform Modernization
- HDFS
- YARN
- Hive
- Spark
- PySpark
- Kafka
- SQL
- Python
- Java
- Scala
- HBase
- MapReduce
- Data Lake
- Data Warehousing
- ETL/ELT
- Data Integration
- Data Quality
- Metadata Management
- Data Lineage
- DataOps
- Master Data
- Data Governance
- Kerberos
- Ranger
- Cloud Adoption
- BFSI