Big Data Analytics Lead

2 days ago


Karachi, Sindh, Pakistan Al Nafi International College Full time
About the Role

We are seeking a highly skilled and experienced Senior Big Data Specialist/Analyst to join our innovative team at Al Nafi International College.

This role is crucial for managing complex data pipelines, integrating data from multiple microservices, and creating actionable dashboards for senior management. The position emphasizes leveraging AIOps processes and procedures, open-source technologies, and cloud-based LLMs and AI models for automation, optimization, and real-time insights.

Key Responsibilities:
  1. Data Pipeline Management:
    Design, build, and maintain robust, automated AIOps-driven data pipelines to collect, process, and analyze data from various microservices.
    Ensure data integrity, accuracy, and timeliness using one-source tools and proactive monitoring.
    Leverage AIOps capabilities for self-healing pipelines, issue detection, and performance optimization.
  2. Dashboard Creation and Maintenance:
    Develop visually engaging, AI-enhanced dashboards using Tableau, Power BI, or Looker.
    Integrate dashboards with LLMs and AI models for predictive analytics and real-time insights.
    Regularly update dashboards to reflect the latest business metrics, KPIs, and trends for senior management decision-making.
  3. Data Integration and Consolidation:
    Aggregate, integrate, and cleanse data from distributed systems and microservices into centralized repositories.
    Implement ETL/ELT processes using AIOps automation tools to standardize data for analysis and visualization.
    Utilize real-time data streaming technologies like Kafka or Flink to enable continuous updates and advanced scalability.
  4. Data Analysis and Reporting:
    Analyze large datasets to uncover trends, patterns, and actionable insights using AI and machine learning models.
    Collaborate with cross-functional teams to translate business needs into technical solutions.
    Provide predictive and prescriptive analytics using AIOps-enhanced frameworks.
  5. Technical Leadership:
    Stay updated on the latest Big Data technologies, AIOps frameworks, and best practices.
    Mentor junior team members on Big Data analytics, AIOps, and AI-driven tools.
    Contribute to strategic planning for cloud-native, AI-driven data infrastructure initiatives.
Qualifications and Skills:
  • Diploma in AIOps (RQF Level 6) or BSc/MSc in Data Science, Computer Science, or a related field.
  • Diploma in AIOps from Al Nafi, with Merit or Distinction, and completion of all Al Razzak program requirements will be given high priority and exempted from the 5+ years of experience requirement.
  • For non-AIOps diploma holders: Minimum of 5+ years of experience in Big Data engineering, data analysis, or similar roles.
Technical Expertise:
  • Proficiency in Big Data frameworks such as Hadoop, Spark, Kafka, or Flink.
  • Experience with data pipeline tools (e.g., Apache Airflow, AWS Glue) integrated with AIOps monitoring and orchestration.
  • Advanced SQL and familiarity with NoSQL databases.
  • Hands-on experience with data visualization tools like Tableau, Power BI, or Looker.
  • Strong programming skills in Python, Scala, or Java, with experience in AI and ML model integration.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Preferred Qualifications:
  • Expertise in integrating data from microservices architectures using AIOps tools.
  • Strong knowledge of open-source technologies for data analytics and cloud solutions.
  • Knowledge of machine learning, predictive analytics, and AI models for decision support.
  • Experience with one-source tools to ensure seamless data integration and consistency.
What We Offer:
  • Competitive salary and benefits package.
  • Opportunity to work on cutting-edge technologies, AIOps, and AI-driven projects.
  • Collaborative and supportive team environment.
  • Professional development and growth opportunities.
  • Relocation opportunities based on senior management discretion.


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