Data Specialist

Multiple Cities

IBM

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Introduction
As an IBM Application Architect, you directly help clients transform their business  and solve complex problems. You will define the scope and vision for projects that deliver customized solutions using your knowledge of IBM platforms.  You are a technical leader, serving as a liaison among business partners, technical resources, and project stakeholders.

Your Role and Responsibilities
We are looking for a highly skilled Data Specialist to design, build, and maintain robust data solutions across diverse database management systems (DBMS). The ideal candidate will possess extensive experience in data modeling, high-performance data processing, strong encryption protocols, and fault-tolerant, resilient system architecture. You will be responsible for ensuring the efficiency, security, and reliability of data pipelines, databases, and data processing frameworks, contributing to the seamless flow of data within the organization.

Core Responsibilities

  • Design, develop, and optimize data pipelines for structured, semi-structured, and unstructured data across various database types (SQL, NoSQL, distributed databases)
  • Implement high-performance data solutions, focusing on optimizing query performance, data indexing, and storage solutions
  • Develop and maintain data models to support business intelligence, analytics, and data-driven applications, ensuring scalability and data integrity
  • Apply advanced encryption protocols and security measures to safeguard data at rest and in transit, adhering to compliance standards and best practices
  • Ensure system resiliency and fault tolerance through distributed processing frameworks, redundancy, and backup strategies, minimizing data loss and service interruptions
  • Diagnose and resolve complex data-related issues, including data integration, data quality, and system performance bottlenecks
  • Collaborate with cross-functional teams, including data scientists, software engineers, and IT operations, to implement data solutions that align with business goals
  • Develop automated processes for data ingestion, transformation, and monitoring, using ETL tools, scripting, and cloud-native data services
  • Conduct continuous monitoring and performance tuning of databases and data processing systems, using tools for real-time alerting, logging, and anomaly detection


Required Technical and Professional Expertise

  • 5+ years of experience in designing and implementing data solutions, with a focus on high-performance, large-scale environments
  • Proven expertise in working with various database types, including SQL, NoSQL, and distributed databases
  • Strong data modeling skills, including the ability to design and implement normalized and denormalized schemas
  • Proficiency in encryption technologies and secure data handling, including experience with encryption protocols, data masking, and access control mechanisms
  • Experience with data integration tools and frameworks for real-time and batch data processing
  • Knowledge of cloud platforms and cloud-native database services, including serverless computing, data lakes, and containerized data workloads.
  • Strong troubleshooting skills to identify and resolve performance, integration, and data quality issues in complex data ecosystems
  • Ability to work effectively with cross-functional teams, ensuring that data solutions meet business and technical requirements
  • Familiarity with data governance practices, ensuring compliance with data privacy regulations and standards


Preferred Technical and Professional Expertise
Same as above


Key Job Details
Role:Data Specialist Location: Multiple Locations See All Toronto Montreal Category:Infrastructure & Technology Employment Type:Full-Time Travel Required:Some travel may be required based on business demand Contract Type:Regular Company:(0026) IBM Canada Limited – IBM Canada Limitee Req ID:740226BR

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Architecture Business Intelligence Data governance Data pipelines Data quality ETL NoSQL Pipelines Privacy Security SQL Unstructured data

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