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Senior Data Engineer builds and optimizes GCP pipelines—batch and real-time—using BigQuery, Spanner, Airflow, and Dataflow to ensure reliable data ingestion and processing.
Build and deploy AI/ML models to automate business processes and generate insights from ERP data using frameworks like TensorFlow or PyTorch.
Build and maintain scalable data pipelines on Databricks and AWS, focusing on ETL, real-time streaming with Spark/Kafka, and cloud infrastructure optimization.
Builds and maintains automated data pipelines using Spark, Kafka, Airflow, and cloud platforms like Azure or AWS to integrate and process large-scale data for AI-driven analytics.
Senior Data Engineer builds and operates AWS-based financial data platforms, cloud infrastructure, and AI agents for accounting automation, while directly engaging with clients to design and deploy solutions.
Senior Data Engineer builds and scales real-time data pipelines on AWS to process grid sensor data, enabling utilities to meet rising electricity demand from AI data centers and electrification.
Build and optimize big-data pipelines and automated reports to power marketing analytics for a global outsourcing firm.
Lead a team that builds and maintains scalable data pipelines and warehouses for a Philippine bank, using Python, SQL, Snowflake, DBT, and Airflow to ensure clean, reliable data for analytics and decision-making.
Design and maintain data pipelines, ETL processes, and Databricks-based analytics to ensure efficient data flow and quality for Xurpas’s data strategy.
Designs and maintains data pipelines and warehouses, transforming raw data into insights using Oracle, PySpark, and Azure SQL for AI-driven analytics.
Builds and maintains databases and data pipelines using SQL and Python to power real-time analytics and business decisions.
Build and optimize Databricks-based data pipelines in Python, ensuring clean data flow and troubleshooting quality issues while collaborating with cross-functional teams.
Design and build scalable data platforms on AWS, Azure, and GCP, using cloud warehouses, Spark, Kafka, and Python/Java to enable AI-driven analytics for enterprise clients.
Build and maintain scalable ETL pipelines using Azure Data Factory, Synapse, Databricks, and Spark to process and optimize data solutions.
Lead the design and evolution of a robust Data Platform, building certified data products from sales, inventory, logistics and finance datasets to ensure reliable, traceable and actionable business decisions.
Build and maintain AWS-native data pipelines and warehouses for telecom analytics using S3, Redshift, Glue, and Python/SQL.
Design, build, and optimize scalable data pipelines and ETL workflows to support business intelligence and data-driven decisions using Python and SQL.
Lead end-to-end AI model development for CPG, including time-series forecasting, optimization, and generative AI, from data exploration to deployment.
Build and migrate ETL/ELT pipelines on Databricks and AWS for a global fund-services provider, using Delta Lake, Spark, and AWS Glue.
Designs and builds scalable cloud data pipelines, warehouses, and analytics platforms using Python, SQL, Spark, and cloud tools like BigQuery and Snowflake, with optional Gen AI integration.
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