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Lead design and implementation of real-time and batch data pipelines using PySpark, Kafka, and Azure, while optimizing lakehouse storage and mentoring engineers.
Build and maintain ETL pipelines and data storage systems in AWS to power a B2B e-commerce platform serving Pakistani SMEs.
Build and maintain scalable data pipelines for AI systems, including ETL/ELT, data quality checks, and warehouse/lake architectures using Python, SQL, and cloud tools.
Design and build data infrastructure—ETL pipelines, data warehouses, and streaming systems—using Python, SQL, and tools like Airflow, Spark, and Snowflake.
Build and maintain scalable data pipelines and infrastructure to power analytics and AI-driven decisions for a fast-growing delivery logistics platform.
Lead a team building sales-focused data products and AI-driven analytics for a logistics platform, modeling data flows and partnering with sales, product, and marketing teams.
Build and maintain scalable data pipelines and infrastructure to power analytics and AI-driven decisions for a fast-growing delivery optimization platform.
Design and maintain scalable ETL/ELT pipelines and data platforms using cloud tools, SQL, Python/Scala/Java, and big data tech like Spark and Kafka.
Builds and maintains scalable data pipelines and ClickHouse analytics for a logistics and fintech platform, ensuring reliable data flow and high-performance queries.
Senior AI Engineer designs and deploys production-ready ML/LLM models, builds data pipelines, and mentors junior engineers for Devsinc’s client projects.
Build and migrate data pipelines from Hadoop to a modern lakehouse using Spark 3 and Iceberg, ensuring reliable reporting and analytics for core business needs.
Design and build production pipelines to migrate a legacy Hadoop warehouse to a modern lakehouse using Spark, Iceberg, and Airflow for core analytics.
Build and migrate data pipelines from legacy Hadoop to a modern lakehouse using Spark, Iceberg, and Airflow to power core analytics and reporting.
Build and maintain end-to-end data pipelines using Spark and Airflow, containerize code with Docker/Kubernetes, and enforce data quality in a lakehouse architecture.
Build and maintain scalable ETL/ELT pipelines using Python, Snowflake, Databricks, and Azure Data Factory to process and transform data for analytics and reporting.
Build and migrate data pipelines for a large-scale lakehouse platform, moving legacy Hadoop workloads to Spark 3/Iceberg and optimizing complex SQL queries.
Build and scale the core infrastructure for Vectara’s enterprise RAG platform, focusing on backend services, DevOps, and ML workloads using Go, Python, or Java.
Builds scalable data pipelines and AI/ML models in Python/SQL, deploys them via MLOps, and maintains cloud-based data infrastructure for intelligent applications.
Designs and maintains data pipelines using Spark, Airflow, Kafka, and Iceberg tables, deploying via GitLab CI/CD on Kubernetes.
Build and maintain scalable data pipelines and warehouses using SQL, Python, and cloud tools (AWS/GCP/Azure) to feed analytics and ML workloads.
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