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Leads Snowflake migrations and pipelines for enterprise clients, mentors teams on Snowpark/Scala/Spark, and sets best practices for scalable data engineering in a hybrid cloud environment.
Designs and builds scalable data pipelines and Snowflake environments for enterprise clients, migrating legacy Hadoop systems and enforcing clean-code practices.
Lead a team building and optimizing large-scale data pipelines using Spark and Scala, designing robust data architectures for enterprise clients.
Build and maintain data pipelines, cloud infrastructure, and support data scientists in industrializing their models using technologies like Spark, Kafka, and Snowflake.
Build data pipelines and interactive tools to automate analyses for drug discovery, using Python/Java/Scala/C++ and cloud platforms like AWS/GCP.
Build and maintain scalable data pipelines, warehouses, and lakes for public-sector or energy clients using Kafka, Spark, Snowflake, and GCP/Azure.
Build and maintain cloud-based data platforms using PySpark, SQL, and streaming frameworks like Kafka to process and deliver large-scale datasets for analytics.
Build and maintain cloud data pipelines and platforms for clients using AWS, Snowflake, Databricks, and Airflow, primarily in Python and PySpark.
Lead a data engineering project using Databricks, Python, Scala and SQL to modernize clients’ data infrastructure.
Lead Data Engineer builds and scales cloud-based data pipelines and platforms for clients using Python, Spark, or Scala, deploying full infra-as-code in AWS/GCP/Azure.
Build and maintain robust ETL pipelines, cloud data platforms, and databases to support analytics and AI teams using Python, Spark, and cloud services like AWS/Azure/GCP.
Design and build large-scale Big Data pipelines and ETL modules using Python, SQL, Spark, and cloud platforms (AWS/GCP/Azure) to process and integrate data for enterprise clients.
Build and maintain data platforms for financial clients, ingesting and processing data in batch/streaming pipelines using Spark, Kafka, and cloud tools to deliver analytics and insights.
Build and maintain scalable data pipelines using Scala and Spark to process complex datasets for a railway-focused company.
Senior Data Engineer builds scalable Python pipelines and data models in the cloud to turn business needs into actionable insights.
Designs and builds secure data pipelines for large datasets, focusing on ETL, cloud data warehousing, and security-cleared environments.
Data Engineer building scalable data pipelines on Databricks and Spark, integrating data sources and optimizing solutions for clients in a consulting role.
Build and maintain cloud-based data pipelines on Azure, using Spark, Scala, Python, and SQL to feed a DataLake and power cost-tracking dashboards for FinOps.
Build and maintain scalable data pipelines, integrate diverse sources, and support analytics teams with Python/R scripts and cloud-based ETL workflows.
Lead a team building and optimizing large-scale data pipelines using Spark/Scala, Hadoop, Kafka, and related Big Data tools for enterprise clients.
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