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Build and maintain data pipelines and workflows using Python, SQL, and tools like Airflow or DBT to support data-driven decision-making.
Build and maintain scalable data pipelines on Databricks and Azure, integrating diverse sources and enabling analytics and ML workloads with PySpark and Delta Lake.
Build and optimize distributed data pipelines and AI analytics for networking using Spark, Kafka, Delta Lake, and Kubernetes in a cloud-native environment.
Design and maintain scalable data models and ETL pipelines for a global fintech platform, ensuring clean, reliable data for analytics and AI use cases.
Design and build scalable data pipelines and platforms to power analytics and AI solutions using cloud technologies like AWS, Databricks, and Snowflake.
Build and maintain scalable data pipelines in Python and AWS to feed AI platforms and BI tools, ensuring high-quality data for analytics and decision-making.
Build and maintain ML infrastructure for credit-risk systems, deploying models, optimizing pipelines, and improving data quality and observability.
Build and maintain event-driven backend services for a security platform using Kafka and Airflow, ensuring multi-tenant, multi-cloud reliability.
Design and build AI-ready data platforms and ML pipelines for analytics, GenAI, and RAG systems on AWS/Azure/GCP, ensuring production-grade delivery and MLOps practices.
Senior Data Engineer builds scalable Snowflake pipelines and reusable ingestion frameworks for a fast-growing digital bank, optimizing cost and reliability across Singapore and Indonesia.
Lead a data engineering team to maintain cloud data pipelines, warehouses, and lakes, migrating legacy systems to Snowflake and AWS while ensuring stability and performance.
Build and maintain high-volume, low-latency ingestion and retrieval services for Abnormal’s AI-native security platform, ensuring reliable, scalable, and security-critical data handling across global cloud infrastructure.
Senior developer building rail signalling and safety software in Singapore using Python, Java, and cloud tools, mentoring teams and overseeing external suppliers.
Build and maintain ETL/ELT pipelines and PySpark jobs to feed AI and analytics platforms; write SQL, validate data, and troubleshoot issues in a cloud-based data stack.
Build and maintain scalable AWS data pipelines using PySpark, Glue, Step Functions, and Lambda for a fintech client, while automating infra with Terraform and CI/CD.
Build and maintain scalable data systems, design ETL/ELT pipelines, and optimize data quality using AWS, Python, SQL, and Spark for analytics and ML workloads.
Designs and maintains scalable data pipelines and cloud-based data warehouses to feed analytics and AI models, using Python, Spark, Kafka, and cloud platforms like AWS/Azure/GCP.
Designs and maintains scalable data pipelines for clinical and sensor data, integrating ML/NLP/LLM workflows with Spark, Beam, and Airflow on AWS to support healthcare analytics.
Build and maintain AI-powered data pipelines for clinical and sensor data, integrating with cloud platforms and AI algorithms to support healthcare analytics.
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