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Designs and maintains scalable, reliable data pipelines and environments using SQL, NoSQL, Azure Data Factory, and Python.
Build and maintain a secure, scalable Azure-based data lake for a major bank using Python, CI/CD, and DevOps practices while collaborating with data engineers and security teams.
Designs and builds Azure-based data lake infrastructure using Terraform, CI/CD, and pytest to ensure scalable, secure, and reliable data platforms for cloud-native applications.
Builds and improves Databricks’ full-stack SaaS products, focusing on modern UI/UX and scalable data/AI infrastructure for enterprise customers.
Builds modern SaaS data/AI tools using React, Node.js, Python, and cloud infra to deliver delightful UX for SQL analytics, workflows, and developer ecosystems.
Lead Python Engineer designs and builds scalable data-processing back-end services and APIs for client projects, focusing on Python, cloud data platforms, and data pipelines.
Build and scale backend services and data pipelines for mining optimization, using PostgreSQL, geospatial queries, and GCP while collaborating with cross-functional teams.
Designs and implements a Databricks-based data lake and AI platform for a global risk consulting firm, focusing on finance data and self-service reporting.
Lead the design and build of scalable cloud data pipelines and big-data platforms using AWS serverless tools (Lambda, Glue, Athena, EMR/Spark) and Python/SQL.
Build and maintain data pipelines, ETL processes, and data warehouses to feed analytics and BI systems using C++, SQL, and database tools.
Build and maintain scalable data pipelines, ETL workflows, and data models on AWS to power analytics and business insights using Python, SQL, and Java.
Build and maintain ETL/ELT pipelines, integrate sales and ad-platform data, and ensure clean, traceable data for reporting and accounting systems using SQL, Python, and APIs.
Build and maintain ETL pipelines, data warehouses, and databases to support securities trading systems using SQL, Python/Java, MongoDB, and Oracle.
Build and maintain scalable data pipelines using PySpark, Databricks, and Airflow to integrate financial data from APIs, Oracle, and Kafka into a data warehouse/lakehouse.
Build and maintain data pipelines, ETL workflows, and warehouses to feed analytics and BI dashboards for an edtech platform.
Lead a scalable data platform using Airflow, Spark, Kafka, and Kubernetes on AWS/GCP to ingest, process, and serve real-time and batch data for a global fashion ecommerce group.
Build and maintain a modern Azure-based data platform using Data Lake Storage Gen2 and Data Factory to support analytics, AI/ML, and large-scale data processing.
Senior Data Engineer designs and builds scalable GCP data pipelines using BigQuery, Dataflow, and Terraform, while automating DevOps workflows with GitHub Actions and Airflow.
Build and optimize scalable data pipelines and streaming solutions on Microsoft Azure and Databricks to power analytics and operational processes.
Build and maintain scalable data pipelines and applications on Azure Databricks using Python, PySpark, and SQL, while collaborating with cross-functional teams to deliver robust, cost-efficient data solutions.
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