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Build and maintain scalable data pipelines and ETL/ELT processes using Python, Apache Airflow, Spark, and GCP services like BigQuery and Cloud SQL for HSBC’s data platform.
Design and maintain Azure-based data pipelines for security analytics, using Data Factory, Databricks, and DevOps practices to ingest and process data across multi-cloud environments.
Design and maintain Azure Data Factory pipelines for ETL/ELT, orchestrating data flows between Azure SQL/Synapse and other sources while optimizing performance and collaborating with stakeholders.
Design and maintain Azure-based ETL/ELT pipelines using Data Factory and Microsoft Fabric, build secure data models in Power BI, and support analytics for banking clients.
Build and maintain scalable data pipelines and lakehouse platforms using Databricks, Spark, Delta Lake, and Python to support anti-financial-crime analytics and reporting for global PwC clients.
Build and maintain scalable data pipelines and Lakehouse architectures using Databricks, PySpark, and Delta Lake to deliver analytics-ready datasets for GenAI and business use cases.
Lead a team to build and optimize Databricks-based ETL/ELT pipelines using Python/SQL, Delta Lake, and cloud platforms (Azure/AWS/GCP) for large-scale data processing.
Lead a Databricks-based data engineering team to build and optimize ETL/ELT pipelines, Delta Lake tables, and cloud data warehouses using Python, SQL, and Azure/AWS/GCP.
Design and build scalable data pipelines, Data Lakes, and DWHs using BigQuery, Kafka, Airflow, and Kubernetes, with exposure to GenAI integrations.
Build and maintain Mettler Toledo’s data platform, creating scalable pipelines and ensuring high-quality data flows for analytics and AI/ML using Databricks, Snowflake, and Python.
Builds data pipelines, ETL/ELT processes, and full-stack web apps in Python/SQL with React or Angular; maintains time-series databases and Databricks/Spark clusters; sets up real-time monitoring and dashboards.
Build and maintain data pipelines and warehouses using Oracle, PostgreSQL, BigQuery, Informatica PowerCenter, Kafka, and Python to feed analytics and ML workloads.
Build and maintain Azure data pipelines and backend services that power an AI-powered chatbot, using Python, SQL, and cloud-native tools.
Own and evolve Vatix’s AWS-based data warehouse (Redshift, Postgres RDS) and pipelines that power real-time customer dashboards, while setting the technical direction for data engineering and integrating third-party systems.
Design and build scalable AWS-based data pipelines using PySpark and AWS Glue, then monitor and optimize them for performance and reliability.
Senior Azure Data Engineer designs and builds scalable data pipelines using Azure Data Factory, Databricks, and Synapse Analytics to support real-time and batch processing for global IT systems.
Builds and optimizes BI data models, ETL pipelines, and dashboards in Power BI, Qlik Sense, and Snowflake for a European manufacturing company.
Senior Data Engineer builds scalable data pipelines and AI tools using Databricks, PySpark, and Azure Data Factory to process batch and streaming data.
Designs and builds scalable AWS-based data pipelines using PySpark and AWS Glue to process and transform business data into reliable cloud architectures.
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