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Design and build end-to-end data pipelines on Microsoft Azure, using Data Factory, Data Lake, SQL DB and Analysis Services to deliver production-ready analytics and AI platforms.
Build and maintain scalable ETL/ELT pipelines on Databricks (Spark SQL, PySpark, Scala) to feed reliable, high-performance data for analytics and decision-making.
Senior Data Engineer designing and building cloud data pipelines and warehouses on GCP using BigQuery and Dataflow for a consulting team.
Alternant Data Engineer in Sopra Steria’s Data Factory, building and optimizing Big Data pipelines for financial clients using Spark, Python, SQL, and cloud tools like Databricks and Snowflake.
Build and optimize Snowflake-based ELT pipelines, model data, and tune cloud performance for a data engineering team.
Build and optimize ETL/ELT pipelines on Databricks using Spark SQL, PySpark, and Scala, and set up a Lakehouse with Delta Lake for reliable, secure data delivery.
Builds and maintains secure, scalable data pipelines for insurance clients using ETL/ELT tools, cloud platforms, and distributed processing frameworks like Spark and Kafka.
Build and maintain robust data pipelines using Palantir Foundry, Python, PySpark, and SQL to transform large-scale aerospace data into actionable business insights for logistics, maintenance, and operations teams.
Design and maintain scalable data pipelines and architectures (ETL/ELT, data lakes, warehouses) using Python, SQL, Spark, Kafka, and cloud platforms (AWS/GCP/Azure).
Build and optimize Microsoft Azure data pipelines and warehouses for clients, using Azure Synapse and SQL to integrate and analyze data for business intelligence and reporting.
Build and maintain scalable data pipelines on Databricks, integrating batch and streaming sources while ensuring governance, security, and performance for analytics and AI projects.
Build and maintain robust, secure data pipelines for insurance clients using ETL/ELT tools, distributed processing (Spark/Hadoop), and cloud platforms to deliver reliable data for business use cases.
Build and maintain scalable ETL/ELT pipelines on Databricks using Spark SQL, PySpark, and Scala to feed reliable, high-performance data for analytics and decision-making.
Builds and maintains ELT pipelines (Talend/SEMARCHY) and analytical data marts for clients, focusing on SQL and HP Vertica.
Build and maintain scalable ETL/ELT pipelines on Google Cloud Platform, optimize BigQuery warehouses, and automate data workflows with Python, SQL, and Terraform for real-time analytics and business insights.
Designs and builds modern data platforms, migrating systems to Snowflake and implementing ELT pipelines with SQL and data modeling.
Build and maintain ETL/ELT pipelines in Talend and BODS, design BI models in Power BI/BO, and deliver dashboards for an industrial company’s decision-support team.
Build and optimize scalable ETL/ELT pipelines for terabytes of EO/IR video data to feed ML training, ensuring high-throughput processing and reproducible experiments in a fast-paced AI startup.
Build and maintain robust data pipelines on GCP for high-volume clients, using Python, Airflow, and dbt while helping shape internal data standards and mentoring peers.
Build and optimize scalable data pipelines and lakehouse infrastructure (Spark, Databricks, Snowflake) for a SaaS data-management platform, and help kick-start early AI use cases.
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