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Build and maintain ETL pipelines using Python and Azure Synapse Analytics for data warehousing and quality checks, with occasional Power BI reporting.
Designs and maintains ETL pipelines using Python (PySpark) and Azure Synapse Analytics to move and transform data for analytics.
Architect and build scalable data pipelines and Snowflake warehouse schemas using Airflow/Prefer/Dagster, enforcing DataOps and software engineering best practices.
Design and build cloud-native data platforms and modern data warehouses for US clients, enabling future AI/LLM integrations and automated workflows.
Designs and builds ETL pipelines using PySpark and Azure Synapse Analytics to move and transform data for analytics and reporting.
Build and optimize reliable, scalable data pipelines using Python, SQL, PySpark, and Azure tools to feed analytics and AI models for enterprise clients.
Build and maintain cloud-based data pipelines and warehouses using SQL, Python, Snowflake, and AWS to power analytics and reporting for clients.
Designs and optimizes data architectures for a global tech firm, transitioning legacy systems into scalable, high-performance data ecosystems using SQL, Python, and cloud warehousing.
Build and optimize Azure-based data pipelines and warehouses, using SQL, Azure Synapse, and Power BI to deliver clean, governed data for reporting and analytics.
Senior role managing Databricks environments, Delta Lake tables, and multi-cloud data pipelines using Python, SQL, and PySpark for reliable data delivery.
Design and maintain ETL workflows using SAP BODS, build scalable data pipelines, and optimize SQL/Teradata queries for data transformation and migration.
Design and maintain ETL pipelines using Python (PySpark) and Azure Synapse Analytics to move and transform data for analytics and reporting.
Builds and maintains data pipelines and ingestion frameworks in a data lake, using Databricks/Spark and SQL to support Power BI reporting and ensure regulatory compliance.
Design and optimize Azure-based data pipelines using PySpark, SQL, and Databricks, and warehouse data in Snowflake while enforcing governance standards.
Designs and optimizes data pipelines, ETL processes, and SQL-based data models for analytics, using big data tech and cloud resources.
Builds and maintains data pipelines and ETL workflows in a data lake, using Databricks, Spark, and SQL to ingest and transform structured, semi-structured, and unstructured data for reporting.
Design and maintain scalable data pipelines and cloud architectures, transforming raw data into insights for strategic decisions.
Designs and builds scalable data pipelines on Google Cloud Platform (BigQuery, Data Fusion, Airflow) to support HR analytics and business decision-making.
Build and maintain ETL pipelines in Azure Synapse using PySpark and SQL to extract, transform, and load data from APIs, databases, and files into scalable data warehouses.
Designs and builds secure, scalable data pipelines and APIs to collect, validate, and govern enterprise data across cloud platforms like AWS and Azure.
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