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Lead a team of data engineers to design and deliver scalable data platforms and pipelines for AI innovation projects, using Azure, Databricks, Spark, and Python.
Design and maintain data pipelines in Microsoft Fabric, model data for Power BI, and build dashboards to support financial services stakeholders.
Build and optimize Databricks-based data pipelines for mining analytics, ensuring data integrity and enabling self-service access across South American teams.
Designs and builds scalable market-data pipelines and APIs for trading, pricing, and risk systems using Python, Spark, Kafka, Databricks, and Snowflake.
Build and maintain scalable data pipelines and warehouses for Frostbite’s quality-engineering telemetry, enabling ML and engineering teams to analyze game-creation data efficiently.
Principal Data Engineer builds and scales Azure-based data pipelines, lakes, and analytics platforms using Databricks, PySpark, and Azure services to deliver governed data solutions for clients.
Design and maintain scalable ETL pipelines on GCP using Spark Serverless, Spark on GKE, and Python, with BigQuery, CloudSQL, and Pub/Sub for data processing and governance.
Principal Data Engineer designs and maintains self-hosted data infrastructure, optimizes PostgreSQL/MongoDB systems, and builds scalable ETL pipelines for a game developer.
Lead a team building and scaling Azure Data Factory and Databricks pipelines in Brampton, handling ingestion, transformation, and loading while ensuring data quality and security.
Lead the design and build of scalable Azure data pipelines and data lake solutions using Databricks, PySpark, and SQL to migrate and process enterprise data.
Lead a team of data engineers to design, build, and optimize scalable data pipelines and warehouses that power analytics and decision-making for a wealth-management firm.
Principal engineer building scalable data pipelines and microservices to power Autodesk’s generative AI and deep-learning tools for architecture, engineering, and construction workflows.
Build and scale a data platform from the ground up, designing pipelines, models, and orchestration to enable reliable analytics and decision-making across the company.
Senior Data Engineer builds and optimizes large-scale data pipelines for Samsung’s cloud services and devices, processing TBs of data daily using AWS, Spark, Kafka, and Python.
Builds and maintains data pipelines and analytics-ready datasets in Snowflake and Power BI for large capital-infrastructure programs, using Azure Data Factory to ingest and transform messy data from ERP, PMIS, and external sources.
Lead and build cloud data pipelines using Python, PySpark, SQL, and Databricks for enterprise banking systems, ensuring efficient ingestion, transformation, and analytics at scale.
Build and maintain front-office systems for commodities trade risk assessment, including market data ingestion, time-series frameworks, and ETL pipelines in Python.
Design and optimize Snowflake-based data architectures, build scalable ETL/ELT pipelines, and model data warehouses to support analytics and reporting.
Build and scale high-throughput data pipelines and infrastructure for Lime’s global micromobility fleet, enabling analytics, ML models, and real-time business intelligence using Python, SQL, Spark, and cloud tools.
Lead a team that builds and operates the shared data platform (Databricks, dbt, GCP) and observability foundations that power analytics, AI, and customer-facing data products at a global supply-chain orchestration company.
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