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Designs and maintains data pipelines using Spark, Airflow, Kafka, and Iceberg tables, deploying via GitLab CI/CD on Kubernetes.
Build and optimize data pipelines and transformations on a Microsoft Fabric Lakehouse using PySpark and Power BI to deliver reliable analytics and reporting.
Build and maintain ETL pipelines in Python, PySpark, and SQL to transform large datasets and automate data workflows for analytics and reporting.
Build and run Azure-based data lakes and Spark pipelines, model data for Power BI, and enforce governance and quality in a large-scale digital transformation.
Senior Data Engineer designs and builds scalable data pipelines, warehouses, and analytics models for enterprise clients using cloud platforms like Azure, AWS, or GCP.
Builds and maintains data-driven applications, REST/GraphQL APIs, and cloud pipelines using Python, SQL, Snowflake, Dagster, dbt, and PySpark.
Builds and optimizes AWS-based data pipelines and lake architectures using PySpark, SQL, and Delta Lake to enable reliable, data-driven decisions.
Lead the design and scaling of data pipelines using Databricks, PySpark, AWS, and SQL while mentoring engineers and aligning with product and engineering stakeholders.
Designs and maintains ETL pipelines using Python (PySpark) and Azure Synapse Analytics to integrate data for analytics and reporting.
Design and run data pipelines from CRM sources to a Databricks-based warehouse using dbt and Airflow, with Python/PySpark in an AWS S3 data lake.
Designs scalable data pipelines and migrates analytics workloads from Redshift to a Databricks Lakehouse on AWS using PySpark and Spark.
Designs and builds large-scale data pipelines using PySpark and Scala, focusing on real-time ingestion and data quality for global clients.
Design and maintain ETL pipelines using Python (PySpark) and Azure Synapse Analytics to move and transform data for analytics and reporting.
Designs and builds scalable cloud data pipelines and lake architectures using Python, PySpark, SQL, and AWS tools like Glue, Athena, and Redshift.
Designs and maintains scalable ETL pipelines on Databricks, building lakehouse architectures with PySpark and SQL to deliver analytics-ready datasets.
Build and optimize cloud data pipelines and databases using SQL, Python, and Azure tools to support analytics and reporting for clients.
Build and maintain ETL pipelines in Azure Synapse using PySpark and SQL, design data warehouses, and ensure reliable data flows for analytics.
Designs and builds scalable Azure-based ETL/ELT pipelines using Databricks, PySpark, and SQL to feed data lakes and warehouses for reporting and analytics.
Designs and maintains scalable data pipelines in Azure and Microsoft Fabric using Python and PySpark to power analytics and AI/ML workloads for a large furniture retailer.
Designs and optimizes ETL pipelines in Azure Synapse using PySpark, ensuring scalable data integration and governance for analytics and reporting.
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