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Added 8 mins ago
AI
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…strategic direction using data platforms, reporting, self-service analytics, real time intelligence and AI…
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Added 23 mins ago
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Added 23 mins ago
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Zodiac Solutions, Inc

Enterprise Data Architect

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 7, 2026
Experience: 14+ years of experience in Enterprise Data Architecture, Hadoop Ecosystem, Big Data Engineering, and Data Platform Modernization.
Posting language: English
Posted: Oct 8, 2026

Original job description

Skills Required:

Must to Have:

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.

Roles and Responsibilities:

Engage with business and technology stakeholders to understand business objectives, data platform requirements, and modernization goals.

Define end-to-end architecture for Hadoop and Big Data platforms supporting analytics, reporting, and AI workloads.

Design scalable, secure, and high-performance Hadoop ecosystems using HDFS, YARN, Spark, Kafka, Hive, and related technologies.

Architect data ingestion, batch processing, streaming, and data lake solutions for enterprise-scale environments.

Define data models, data lake zones, governance frameworks, metadata management, lineage, and security standards.

Lead Hadoop modernization, migration, and platform optimization initiatives to improve performance, scalability, and operational efficiency.

Establish architecture standards, reusable frameworks, engineering best practices, and DataOps operating models.

Provide technical leadership across solution design, implementation, testing, migration, deployment, and production support activities.

Conduct architecture reviews, identify risks and dependencies, and guide teams on mitigation strategies and best practices.

Drive performance tuning, capacity planning, reliability improvements, and infrastructure cost optimization.

Collaborate with data engineers, platform teams, architects, vendors, and client stakeholders to deliver enterprise data solutions.

Support solutioning, RFP responses, effort estimation, technical presentations, and client workshops.

Mentor architects and engineers and contribute to hiring, capability development, and knowledge-sharing initiatives.

Develop reusable accelerators, reference architectures, implementation frameworks, and technical best practices for Big Data platforms

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More about this job

Responsibilities

Define and lead secure, scalable Hadoop and Big Data architectures for analytics, reporting, and AI, including data ingestion, batch and streaming processing, governance, and modernization. Provide technical leadership across delivery and production support, guide architecture reviews and optimization, collaborate with stakeholders, and mentor teams while developing reusable frameworks and reference architectures.

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. Candidates should also bring experience in data engineering, governance and security, architecture and migration planning, platform modernization, and BFSI regulatory requirements; relevant certifications are preferred.

Skills

Enterprise Data Architecture
Hadoop
HDFS
YARN
Spark
PySpark
Kafka
Hive
Python
SQL
Java
Scala
Big Data Engineering
Data Lake Architecture
Data Governance
DataOps

Visa sponsorship

Not detected in the job text

Keywords

Enterprise Data Architecture
Hadoop
HDFS
YARN
Hive
Spark
PySpark
Kafka
HBase
MapReduce
SQL
Python
Java
Scala
Big Data Engineering
Data Lake
Data Warehousing
ETL/ELT
Data Integration
Data Quality
Metadata Management
Data Lineage
DataOps
Data Governance
Kerberos
Ranger
Cloud Adoption
Platform Modernization
BFSI
Architecture Design

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