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Build and maintain scalable data pipelines and cloud infrastructure (GCP/AWS/Azure) to process large datasets, using SQL and Python for ETL and data quality monitoring.
Design and build cloud-based data pipelines and AI analytics platforms for clients, using tools like Snowflake, AWS Redshift, and Apache Airflow to ingest, process, and transform data at scale.
Design and maintain Azure Fabric data pipelines (Bronze–Silver–Gold) to transform raw data into analytics-ready datasets for Power BI Embedded reports.
Designs and builds scalable GCP-based data pipelines using Dataflow, Pub/Sub, and BigQuery to ingest, process, and store batch and streaming data reliably.
Design and optimize Snowflake-based data ingestion pipelines and ETL workflows using SnowPipe, dbt, and GitHub to deliver scalable analytics platforms for enterprise clients.
Design and build Snowflake-based data pipelines and ETL processes, optimize performance, and implement GenAI use cases using Snowflake Cortex.
Senior Data Engineer builds and maintains Azure-based data pipelines and warehouses using Databricks, Azure Data Factory, SQL, and Python to power BI reports and global analytics.
Designs and builds Snowflake-based data pipelines using SnowPipe and dbt for ingestion, transformation, and governance across ANZ clients.
Build and optimize Snowflake data pipelines, ETL/ELT workflows, and GenAI integrations using Snowpark and Cortex AI features.
Build and scale production-grade data pipelines and Lakehouse infrastructure using Azure, Databricks, Python, and Spark to power analytics and AI for enterprise risk and financial advisory services.
Builds end-to-end data pipelines in Snowflake and AWS, transforming raw data into AI-ready features for an internal AI platform used across marketing and analytics teams.
Build and deploy AI systems for cost estimation and optimization, including LLM-powered tools and MLOps pipelines integrated with enterprise platforms.
Build and maintain scalable data pipelines on Snowflake using SnowPipe and dbt, ensuring clean, reliable data for analytics and AI/ML workloads.
Designs and builds scalable data pipelines on Azure to ingest, transform, and store healthcare data for analytics using Databricks, Data Factory, and Delta Lake.
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.
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.
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.
Build and maintain scalable data pipelines and warehouses using BigQuery, ClickHouse, Airflow, Kafka, and CDC tools to power analytics and reporting.
Build and maintain scalable data pipelines and cloud infrastructure on GCP/AWS/Azure to process large datasets, using Python, SQL, and big-data tools like Spark and Airflow.
Design and build scalable data pipelines on Snowflake using SnowPipe and dbt, then clean and integrate data to support analytics and AI/ML workloads.
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