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Build and maintain scalable data platforms for a bank’s transformation using Python, SQL, and cloud tools, with ETL/ELT pipelines.
Leads the design and deployment of production-grade AI systems, including multi-agent workflows and RAG architectures, using GCP and MLOps/LLMOps pipelines.
Leads the design and deployment of production-grade AI systems, including multi-agent workflows and RAG architectures, using GCP and MLOps/LLMOps pipelines to scale genAI across global operations.
Build and improve data-driven products for payments and commerce using ML, Python, SQL, and GenAI to extract insights from loyalty, digital, and basket data.
Designs and implements enterprise-scale data architecture for a large transport business, ensuring scalable, secure BI and analytics across multiple countries using AWS, Databricks, and Snowflake.
Build and maintain a cloud-based ELT platform to process large-scale behavioural data, enabling data-driven marketing insights across multiple websites.
Senior Software Engineer builds and optimizes cloud-based data pipelines and warehouses to turn raw user data into actionable insights for analysts and business teams in a large e-commerce company.
Build and maintain scalable data pipelines and warehouses using SQL, Python, Snowflake, and ETL/ELT tools for finance-focused clients.
Build and maintain production-grade data pipelines that integrate operational systems (MES, historians, instruments) into a governed, analytics-ready foundation for biopharma manufacturing.
Own and evolve VALR’s data platform, building scalable ELT pipelines and ensuring data quality for a fast-growing crypto exchange using GCP/BigQuery.
Designs and maintains scalable GCP data pipelines and warehouses (BigQuery, Dataflow) to feed analytics and ML, using SQL, Python, Airflow, and Kafka.
Design and optimize SQL-based ETL pipelines for financial data using SSIS, AWS Glue, and Python, ensuring compliance and performance in a regulated environment.
Designs and builds enterprise-scale data architectures, data warehouses, and cloud platforms to support analytics and BI, ensuring governance, security, and performance.
Design and maintain Snowflake-based data pipelines and architectures, ensuring quality and governance while collaborating with stakeholders to prioritize work.
Designs, builds, and maintains Azure-based data pipelines and lakehouse architectures using Databricks, Synapse, and Data Factory to deliver clean, reliable datasets for analytics and AI.
Design and maintain scalable ETL pipelines, data warehouses, and real-time streaming solutions using SQL, Python, and cloud platforms like AWS/Azure/GCP.
Design and maintain scalable data pipelines and infrastructure using Spark, Kafka, and cloud tools to process large datasets for enterprise clients.
Build and maintain scalable data pipelines and ETL/ELT processes using Python, SQL, and cloud platforms (AWS/Azure) to support analytics and AI-driven products.
Build and maintain scalable data pipelines and warehouses for analytics and ML, integrating multiple sources using Python, SQL, and cloud tools.
Designs and maintains scalable data pipelines using Python, SQL, Spark, and Azure tools to feed analytics and AI systems.
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