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Lead a team to design and build scalable data pipelines using Spark/Scala, Airflow, and cloud platforms, while mentoring engineers and ensuring regulatory compliance.
Senior Data Engineer builds scalable pipelines to process billions of market data records for trading systems using Python, SQL, Spark, and Kafka.
Lead a team to design and build scalable data platforms (Data Lakes, pipelines) using Python, SQL, Spark, and GCP, while mentoring engineers and aligning architecture with business needs.
Build and maintain AWS cloud infrastructure for a smart metering platform that processes large IoT data volumes, focusing on automation, CI/CD, and Infrastructure as Code.
Build and maintain scalable data pipelines on Databricks, using Python and cloud platforms (AWS/Azure/GCP) to ingest, transform, and secure large datasets for analytics.
Designs and maintains scalable data pipelines on GCP, models data in BigQuery, and optimizes queries and costs using Airflow, Terraform, and BI collaboration.
Design and build scalable ETL pipelines and data models using Spark, Scala, and cloud storage (AWS S3, Hive) to power analytics and BI tools like Databricks and Power BI.
Build and maintain scalable data pipelines and platforms using Azure, Databricks, PySpark, and Python to enable analytics and AI workloads.
Design and build scalable data pipelines and applications for regulatory reporting in a global investment bank, using Python, Databricks, Spark, and cloud tech.
Design and maintain a cloud-based lakehouse on AWS, building real-time ingestion pipelines with Kafka/Debezium and PySpark, and curating trusted analytics layers for fintech decision-making.
Designs and builds large-scale data pipelines and lakes using Python, SQL, and big-data tech, collaborating with global teams on data projects.
Builds and optimizes cloud data lakes and pipelines using Python and SQL to enable modern data infrastructure.
Designs and maintains Big Data pipelines, data warehouses, and analytics platforms using Spark, Hadoop, and cloud tools to enable data-driven business decisions.
Build and scale AWS-based data lakes and pipelines for a fintech platform and an AI-powered recruitment assistant.
Junior DevOps Engineer maintains AWS cloud infrastructure, Kubernetes clusters, and CI/CD pipelines for a global fintech client, using AWS CDK, Jenkins, and CloudWatch.
Lead a team of senior engineers building and enhancing software products for a global client using Node.js, Next.js, and AI-assisted development tools while owning architecture and client engagement.
Design and migrate on-prem data pipelines to AWS using Glue, Redshift, EMR, and Python; automate workflows with Airflow and monitor with CloudWatch/Kibana.
Build and optimize scalable data pipelines and cloud-native apps using Snowflake, Databricks, Python and SQL to power reporting, analytics and operational processes for financial clients.
Build and maintain data pipelines for analytics, using Python, PySpark, SQL Server, and Azure Data Lake to support travel-industry decision-making.
Build and own a GCP-based Medallion lakehouse and ML data pipelines for training, inference, and monitoring at scale.
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