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Build and optimize data pipelines using Snowflake, Databricks, Python, and SQL to deliver scalable analytics solutions for financial clients.
Build and deploy ML models and pipelines using Python, TensorFlow/PyTorch, and MLOps tools; analyze data to drive business decisions.
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.
Build and optimize petabyte-scale data infrastructure for AI training, using Python, Kubernetes, and distributed systems to ensure data integrity and performance.
Build and maintain scalable data pipelines using Python, DBT, and cloud warehouses (Snowflake/Azure) to power analytics and business decisions.
Build and maintain scalable ETL/ELT pipelines and data warehouses to track USDC movement across blockchains, enabling analytics on holdings, use cases, and growth opportunities.
Leads the data engineering team to build scalable pipelines and data infrastructure for payments, risk, and product analytics using Iceberg, Kafka, Flink, Spark, Airflow, and AWS.
Principal Data Engineer designs and builds scalable cloud data pipelines using Snowflake, Databricks, and AWS, while integrating AI agents for automated data quality and transformation workflows.
Senior Data Engineer builds and maintains ETL pipelines, schedules jobs, and reviews code for robust data solutions in a consulting context.
Principal Data Engineer designs and maintains self-hosted data infrastructure, optimizes PostgreSQL/MongoDB systems, and builds scalable ETL pipelines for a game developer.
Leads data pipelines and platforms for payments, risk, and analytics using Iceberg, Kafka, Flink, Spark, and Airflow on AWS.
Build and optimize cloud data pipelines and warehouses (Snowflake/BigQuery) to power AI-driven analytics and BI for global consumer brands like NFL and Lululemon.
Build and own petabyte-scale ETL pipelines for multi-sensor data to generate high-definition maps used by Waabi’s autonomy software and AI-driven simulator.
Lead a data engineering and analytics team to build scalable pipelines, warehouses, and KPI frameworks that turn raw data into trusted business insights for a fintech startup.
Lead a data engineering and analytics team to build scalable data infrastructure and AI-powered analytics for a robotics-based delivery startup, ensuring reliable, governed data products for cross-functional decision-making.
Build and maintain ETL pipelines in Scala/Spark to move and validate accounting data into a central data lake, using Databricks, Azure, and Agile practices.
Lead Faire’s Core Data Infrastructure team to build data models and pipelines that inform product decisions, using SQL, Python/Java, and BI tools like Looker to drive insights for SMB-focused ecommerce growth.
Lead the design and build of large-scale data pipelines and platforms using PySpark, GCP, and Airflow to power analytics, AI features, and real-time measurement for a major retail and media company.
Build and optimize large-scale data pipelines and real-time dashboards using Java, Scala, Python, and GCP tools to support analytics and reporting for a retail-focused product team.
Build and own Flinks’ data and ML platform: BigQuery, dbt, Airflow, Pub/Sub, Kubeflow, Vertex AI, and FastAPI to turn models into production-grade services.
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