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Senior Data Engineer 

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General Details
Advertised By:Agency
Company Name:Executive Placements
Job Type:Full-Time
Description
JOB OUTPUTS AND KEY PERFORMANCE INDICATORS
  • Design, build, and maintain ELT pipelines
  • Pipeline success rate (% jobs completed without failure)
  • Data latency (extraction to availability)
  • Error resolution turnaround time
  • Integrate data across systems (WMS, TMS, ERP, IoT)
  • Number of successful system integrations
    % data completeness and consistency across sources
  • Average time to onboard new data source
  • Data Lake / Warehouse Management
  • System uptime and availability
  • Query performance (execution speed)
  • Storage usage vs capacity
  • Structured and clean data sets
  • Data quality score (accuracy, completeness, validity)
  • Number of reported data issues
  • Resolution turnaround time
  • Collaboration with BI and Data Science teams
  • Time to deliver datasets for reports and models
  • Internal stakeholder satisfaction rating
  • Support requests resolved within SLA
  • Documentation and data cataloguing
    % of pipelines with up to date documentation
  • Metadata completeness
  • User ease of data discovery
  • Security and compliance support
    % compliance with access control policies
  • Number of unauthorised access incidents
  • Audit readiness and completion rate
  • Process automation
  • Manual hours reduced via automation
  • Number of recurring tasks automated
  • Stability of automated workflows
  • Issue analysis and root cause investigations
  • Time to issue resolution (from investigation to recommendation)
  • Number of root causes correctly identified
  • Reduction in repeated issues
  • Advanced SQL development, optimisation and data engineering
  • Query performance improvements (execution speed and efficiency)
  • SQL based data validation, transformation and cleansing coverage
  • Reusable SQL pipelines for recurring logistics workflows (inventory, shipments, routing)
  • SQL based reconciliation across multiple systems
  • Version controlled, documented SQL scripts aligned with governance standards
  • Reduction in errors or rework due to SQL inefficiencies
JOB SPECIFIC REQUIREMENTS
  • Minimum Requirements (Experience and Qualifications)
  • Bachelor's or Masters in Computer Science or related field
  • Microsoft Certified Azure Data Engineer Associate
  • Google Professional Data Engineer
  • AWS Certified Data Analytics
  • Certifications in BI or analytics tools such as Power BI, Tableau or SQL
  • 3 to 5 years experience in data engineering preferably in logistics or supply chain sectors
  • Required Knowledge
  • Development of ELT and ETL pipelines using tools such as Apache Airflow,
  • SSIS or Azure Data Factory
  • Data integration across logistics systems including ERP, WMS, TMS and IoT

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Executive Placements
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