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Build and scale ELT pipelines for iGaming using Airflow, dbt, Python, and AWS, transforming raw data into reliable datasets for analytics and BI teams.
Build and maintain Azure-based data pipelines and analytics solutions using Microsoft Fabric, Azure Data Lake, and Azure Data Factory.
Designs and builds scalable AWS data pipelines, data lakes on S3 with Apache Iceberg, and Airflow workflows for CDC and batch ingestion from DynamoDB, Aurora PostgreSQL, and Neptune.
Build and maintain data pipelines using Azure Data Factory and Databricks, ensuring clean, accessible data for analytics and ML while collaborating with data scientists and stakeholders.
Design and build cloud-based data pipelines and analytics solutions on Azure, Microsoft Fabric, and Databricks for enterprise clients, using Python, PySpark, and SQL.
Build and run a cloud-based data lakehouse platform for a fintech client, automating deployments, monitoring performance, and optimizing Kubernetes clusters with tools like Dremio, Spark, and Prometheus.
Senior Data Engineer builds and optimizes AWS-based data pipelines, ETL workflows, and cloud data lakes/warehouses to modernize infrastructure and migrate large-scale datasets.
Build and optimize large-scale data pipelines and integrate LLMs into production systems for Docusign’s Intelligent Agreement Management platform.
Build and maintain scalable data pipelines and cloud-based analytics platforms using Azure, PySpark, and Power BI to power MetLife’s global insurance and financial services.
Lead a team building and optimizing data pipelines in Teradata for a major bank, ensuring reliability and performance while mentoring engineers and collaborating with stakeholders.
Designs and builds scalable AWS cloud data platforms, including ETL/ELT pipelines and data lakes, to deliver clean, BI-ready datasets for analytics teams.
Designs and maintains data pipelines, warehouses, and analytics infrastructure using SQL, Python, and AWS services to support reporting and modeling for clients.
Build and maintain data pipelines and lakes to support analytics for Nexperia’s global semiconductor manufacturing operations, using Spark, Kafka, SQL, and Python.
Builds and maintains Microsoft BI solutions using Azure Synapse, Power BI, and SSAS for clients, focusing on ETL, data modeling, and visualization.
Designs and maintains Azure-based data pipelines using Synapse, Data Factory, and Data Lake Gen2 to deliver scalable, enterprise-grade ETL solutions.
Build and optimize Azure Databricks/Spark pipelines and ETL frameworks to ingest, transform, and load enterprise data into scalable Azure data lakes and warehouses.
Design and maintain Azure-based data pipelines and lakehouse solutions using Synapse, Data Factory, and Informatica to power analytics and reporting for a government client.
Build and run AWS/Snowflake data pipelines for a global mobility operator, industrializing a new Data Lake and supporting analytics teams with curated datasets.
Lead the design and maintenance of a data lake and warehouse, ingesting structured/unstructured data, and mentoring a team of data engineers using Azure Data Factory, Databricks, and Python.
Build and maintain Spark pipelines and Kafka ingestion for large-scale government data lakes, ensuring data quality and real-time processing.
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