Saeed Ameed

* Lead data platform, BI, and AI-integrated engineering initiatives across a 20-member multidisciplinary team, scaling the organization from 7 to 20 team members while improving delivery capacity and technical ownership.
* Designed and governed real-time and batch data architecture across Data Lake, Data Warehouse, and Data Mart layers, supporting analytics, reporting, AI workloads, and operationa

* Scaled the data engineering team from 3 to 7 members, owning technical direction across ELT/ETL development, orchestration, infrastructure, data operations, and platform reliability.
* Designed and operated a distributed data platform ingesting more than 1 TB of data per day with 99.9% SLA availability for analytics, reporting, and AI-driven use cases.
* Built high-volume telemetry and state-col

* Maintained and optimized distributed blockchain infrastructure for international cryptocurrency exchange environments.
* Improved platform reliability, throughput, and operational resilience for high-volume transaction processing across multiple markets.
* Supported infrastructure monitoring, performance tuning, and operational troubleshooting for blockchain-related data and transaction systems.

* Led engineering and IT teams across system architecture, software development, infrastructure operations, and production support for a cryptocurrency exchange platform.
* Designed and deployed a microservices-based exchange architecture integrated with full-node blockchain infrastructure.
* Improved platform scalability, security, and operational reliability for high-volume financial transaction

* Led development and maintenance of a microservices-based data collection platform aggregating data from social media, e-commerce, and external digital sources.
* Built and operated streaming ingestion pipelines using Apache Kafka to support scalable collection, processing, and delivery of high-volume datasets.
* Integrated AI-processed data into Elasticsearch, enabling fast querying, analytics,

* Redesigned distributed data analysis systems to improve scalability, performance, reliability, and maintainability.
* Advised on architecture improvements across distributed storage, processing engines, graph databases, and search infrastructure.
* Optimized data workflows for analytical workloads using Spark, HBase, Phoenix, PostgreSQL, Elasticsearch, Redis, and graph database technologies.
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* Operated, maintained, and optimized a large-scale Hadoop ecosystem across multiple clusters, supporting distributed storage, batch processing, and streaming workloads.
* Improved batch and stream processing stability through performance tuning, capacity planning, and troubleshooting across Hadoop, Spark, HBase, and related services.
* Supported data infrastructure reliability by monitoring clust

* Developed data-driven applications and backend components for storage, processing, and analytical workloads using Java and Scala.
* Built integrations between application services and distributed data infrastructure, supporting ingestion, transformation, and consumption of large-scale datasets.
* Collaborated with data engineering teams to improve platform performance, maintainability, and opera

* Built data preprocessing and ingestion pipelines for large-scale analytics workflows.
* Developed backend components in Java and Scala to support data transformation, validation, and integration requirements.
* Worked with PostgreSQL, Hadoop HDFS, Apache NiFi, and Apache Spark to support distributed processing and analytical use cases.
**Key Technologies:** Apache NiFi, PostgreSQL, Hadoop HDFS,

* Provided technical network and application support for broadband network management and ADSL service operations.
* Supported MikroTik and related network equipment, troubleshooting connectivity, latency, and service reliability issues.
* Maintained an internet accounting and bandwidth-management platform used to capture, process, and report user consumption data for billing and analytics.
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