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    Data EngineeringTelecommunications Leader9 months32 engineers

    Data Engineering Pipeline Transformation

    Built enterprise-scale data engineering platform for telecommunications company, processing 10TB+ daily data with real-time analytics and machine learning capabilities.

    • 10TB+

      Daily Data Processed

    • 90%

      Performance Gain

    • $1.9M

      Operational Savings

    The challenge

    • Legacy ETL processes causing 12+ hour delays
    • Inconsistent data quality across multiple sources
    • Need for real-time customer analytics and reporting
    • Scaling data processing for 50M+ customers

    What we did

    • Implemented streaming data pipeline with Apache Kafka
    • Built data quality framework with automated validation
    • Created real-time dashboard with sub-second response times
    • Designed auto-scaling data processing on Kubernetes

    The results

    • Real-time data processing with <1 minute latency
    • 90% improvement in data processing performance
    • 99.9% data quality accuracy across all pipelines
    • Enabled real-time customer insights and personalization
    Apache SparkKafkaSnowflakePythonScalaAirflowKubernetesGrafana
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    50+
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    6 Months
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    $2.1M
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    AWS
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    Terraform
    Docker
    Jenkins
    Python
    Java
    PostgreSQL
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