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Role Overview We are seeking a part-time Python/Django Developer & Data Engineer with experience in DevOps and CI/CD pipelines to join our growing team. This role supports the maintenance and evolution of our data…
Build and optimize Snowflake-based ETL/ELT pipelines, tune queries, and maintain cloud data platforms for enterprise clients in a managed-services role.
Build and maintain large-scale data pipelines using Azure Databricks, PySpark, and SQL to process TB-scale datasets for a multinational insurance provider.
Design and build AWS-based data platforms, including data lakes, warehouses, and pipelines, while providing architectural oversight and ensuring security and cost optimization.
Designs and builds scalable data pipelines and warehouses on Google Cloud, focusing on ETL/ELT, real-time ingestion, and DataOps practices.
Build and maintain data pipelines for trade and communications surveillance, ensuring regulatory compliance and data quality across AWS infrastructure.
Build and maintain cloud-native AWS data platforms, ETL/ELT pipelines, and data lakes to support analytics and BI use cases.
Builds and maintains databases and data pipelines using SQL and Python to power real-time analytics and business decisions.
Build and optimize Snowflake-based ETL/ELT pipelines, tune queries, and maintain cloud data platforms for enterprise clients in a managed-services setting.
Design and build scalable ETL pipelines using Snowflake, SnowPipe, and dbt to ingest, transform, and deliver clean data for analytics and business insights.
Design and build Snowflake-based data pipelines and governance, using Snowpark/SQL to ingest, transform, and expose data while enabling GenAI features with Cortex AI.
Builds and maintains data pipelines, ETL scripts, and APIs in Python and AWS to clean, process, and warehouse enterprise data for analytics and reporting.
Builds and maintains enterprise data pipelines and analytics platforms using SQL, ETL/ELT, and cloud tools like Microsoft Fabric to support reporting and AI initiatives.
Designs and maintains Microsoft Fabric data pipelines, OneLake environments, and analytics-ready data using Azure services, PySpark, and T-SQL.
Design and build scalable data pipelines and Lakehouse infrastructure using Azure and Databricks, enabling AI/ML and analytics for financial, legal, and government clients.
Builds and maintains scalable data pipelines and lakehouse architectures to feed AI/ML workloads and analytics, using Spark, SQL, Python, and cloud services like AWS.
Designs and maintains Azure-based data pipelines using Databricks, PySpark, and Azure Data Factory to ingest and process banking data into scalable Medallion Architecture layers.
Build and scale enterprise data infrastructure using Azure, Databricks, and Python to power analytics and AI across the firm.
Senior Data Engineer builds and maintains GCP-based data pipelines, ETL workflows, and analytics models for MSP customers, using Python, SQL, and Airflow.
Build and optimize Snowflake-based data pipelines and ETL processes, implement governance and AI features, and tune performance for cloud data workloads.
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