DE&A -Data Engineering Apache

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Design, develop, and implement scalable, resilient, and high-performance data pipelines and data architecturesfor enterprise data platforms. ·      Build and optimize ETL/ELT pipelines supporting batch, near-real-time, and streaming data processing requirements. ·      Design and implement enterprise data ingestion and integration workflows using Apache NiFi, including data routing, transformation, orchestration, monitoring, and integration across heterogeneous data sources and platforms. ·      Develop distributed data processing solutions using Apache Spark with Scala and/or Python (PySpark). ·      Design and implement data solutions across relational database management systems (RDBMS) and modern data lakehouse technologies such as Apache Iceberg. ·      Build and optimize federated and distributed SQL capabilities using Starburst and Trino query engines. ·      Develop event-driven and real-time data processing solutions using Apache Kafka and Spark Streaming / Structured Streaming. ·      Lead end-to-end delivery of enterprise-scale data engineering initiatives involving multiple engineering, product, architecture, and business teams. ·      Strengthen platform reliability through automation, CI/CD, testing, monitoring, observability, documentation, and operational excellence. ·      Improve data quality, performance, scalability, resiliency, and cost efficiency across data platforms and pipelines. ·      Support enterprise data governance by maintai

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