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Department: Data Engineering & Analytics Infrastructure
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Experience Range: 6–10 Years
About the Company & Data Engineering Culture
At the heart of up-to-date supply chain orchestration lies a massive volume of heterogeneous data—ranging from real-time GPS fleet telemetry and warehouse IoT sensor streams to asynchronous purchase orders and ERP ledger entries. As a high-growth Supply Chain Technology SaaS enterprise, our platform processes petabytes of operational data daily.
Our data engineering culture revolves around building immutable, fault-tolerant data pipelines, real-time stream processing architectures, and high-performance data lakehouse foundations. We empower our data science, operations research, and enterprise client reporting squads with pristine, low-latency data models. If you are passionate about architecting massive-scale data systems that drive real-world logistics optimization,
this is your arena.
Position Overview
We are looking for an expert, hands-on Senior Data Engineer to design, build, and scale our next-generation data lakehouse and real-time streaming infrastructure. In this role, you will own the end-to-end data lifecycle—from ingestion and transformation to serving layers that power predictive analytics, machine learning feature stores, and client-facing supply chain visibility dashboards.
You will work closely with software architects, backend engineers, and data scientists to ensure high data quality, lineage tracking, and sub-second query performance across complex, multi-tenant enterprise datasets.
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High-Throughput Pipelines: Design, build, and optimize real-time streaming data pipelines using Apache Kafka, Apache Flink, and Spark Streaming to process high-frequency log