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Lead the design and optimization of scalable Azure data pipelines using Databricks, PySpark, and ADF, while mentoring engineers and collaborating with cross-functional teams.
Designs and maintains cloud-based PySpark pipelines that transform and load large datasets using Python and SQL, ensuring reliability and performance.
Build and maintain scalable data pipelines and analytics datasets using Azure Databricks, Microsoft Fabric, and Python, enabling reporting and AI use cases for enterprise clients.
Build and scale a cloud-native data platform on AWS to power real-time recommendations and analytics for Europe’s leading brands.
Build and maintain cloud data pipelines and analytics platforms using Azure Synapse, PySpark, and SQL for large-scale enterprise projects.
Build and maintain cloud-native AWS data platforms, ETL/ELT pipelines, and data lakes to support analytics and BI use cases.
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.
Build and maintain scalable ETL pipelines using Azure Data Factory, Synapse, Databricks, and Spark to process and optimize data solutions.
Build and migrate ETL/ELT pipelines on Databricks and AWS for a global fund-services provider, using Delta Lake, Spark, and AWS Glue.
Senior Data Engineer builds and maintains HIPAA-compliant data pipelines and models for a healthcare AI product using Python, Dagster, DBT, PostgreSQL, and AWS services.
Lead a team to design and build scalable data pipelines using Azure Databricks, ADF, and PySpark, while integrating with AWS, Snowflake, and BigQuery in hybrid/multi-cloud environments.
Lead the end-to-end data architecture—ingestion, processing, modeling, and consumption—using Python, PySpark, Airflow, and AWS services to enable reliable reporting and LLM-driven analytics at scale.
Designs and maintains Microsoft Fabric data pipelines, OneLake environments, and analytics-ready data using Azure services, PySpark, and T-SQL.
Designs and builds enterprise data pipelines using Microsoft Fabric, Synapse, and Azure Data Factory to power analytics and AI workloads.
Designs and maintains Azure-based data pipelines using Databricks, PySpark, and Azure Data Factory to ingest and process banking data into scalable Medallion Architecture layers.
Builds and maintains PySpark data pipelines on GCP, using BigQuery and Dataproc to process large datasets with Python and SQL.
Build and migrate ETL/ELT pipelines on Databricks Delta Lake and AWS, using PySpark, SQL, and AWS Glue to process batch and streaming data for a global fund-services provider.
Designs resilient, scalable data pipelines and products using Azure, SQL, Spark, and CI/CD to transform and deliver data for analytics and architecture.
Leads design and delivery of cloud-based data platforms using AWS services like Redshift, Glue, and PySpark, ensuring scalable, secure data solutions for analytics and governance.
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