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Lead the architecture and evolution of Kueski’s data platform, designing scalable batch/streaming pipelines and AI-centric solutions while setting engineering standards and mentoring teams.
Lead Power BI dashboard development and SQL-based reporting while maintaining data pipelines and ETL processes to deliver insights for internal teams.
Build and maintain scalable data pipelines for market abuse surveillance, ingesting trade, market, and communications data into AWS and Snowflake while enforcing data quality and regulatory compliance.
Builds and maintains data pipelines to feed AI-driven marketing analytics, enabling audience segmentation and campaign performance analysis.
Design and maintain automated ETL/ELT pipelines to ingest and transform network telemetry into an analytics-ready data mart, while enforcing data quality, governance, and observability.
Design and build Snowflake-based ELT pipelines, ensure data quality, and lead GenAI initiatives using Snowflake Cortex AI features.
Builds robotics data pipelines, trains AI models, and evaluates performance for real-time embodied AI systems in production.
Build and maintain GCP-based data pipelines and analytics for enterprise clients, using Python, SQL, Airflow, and BigQuery to ensure reliable data ingestion and reporting.
Design and maintain scalable ETL/ELT pipelines to ingest and transform network telemetry data into an optimized data mart for analytics, ensuring high availability, data quality, and governance.
Designs and maintains AWS-based data pipelines and cloud infrastructure using Python, SQL, and AWS services like Glue and Lambda to build scalable, secure data solutions.
Builds and maintains large-scale data pipelines on Azure Databricks and Spark, writing PySpark/Python and SQL to process TB-scale datasets and ensure data quality.
Builds and maintains scalable data pipelines to feed AI models, ensuring clean, reliable data for decision-making in a hybrid office setup.
Design and maintain scalable data marts and ELT pipelines using DBT, Fivetran, and SQL to power analytics for e-commerce and logistics platforms.
Build and maintain scalable data pipelines and ETL processes using Python and SQL to support analytics and data science teams.
Designs, builds, and maintains data pipelines and analytics infrastructure using SQL and visualization tools in a hybrid Manila office.
Build and maintain scalable batch and streaming data pipelines in AWS + Databricks, using Python, SQL, and modern lakehouse architectures to power analytics and reporting for a fast-growing fintech lender.
Builds and maintains scalable data pipelines and ETL processes in AWS using Python and SQL to ensure reliable analytics and data availability.
Designs and maintains data infrastructure and pipelines using Apache Kafka, Spark, and Airflow to support AI/ML and BI workloads.
Builds and maintains data pipelines for AI training and analytics using Databricks, GCP, and Azure, ensuring clean data for models and reporting.
Build and maintain scalable data pipelines using Databricks, GCP, and Azure to power AI model training, RAG-based search, and enterprise analytics.
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