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Build and maintain the data warehouse, semantic layer, and quality pipelines that power Stand’s AI-driven risk engine and underwriting decisions, migrating from Postgres to a scalable analytics platform with dbt, orchestration, and reconciliation.
Build and deploy AI models for human-like conversations, spanning speech, language, and real-time inference systems. Own end-to-end ML pipelines and MLOps tooling in a fast-moving startup.
Senior Data Engineer builds and optimizes scalable AWS data pipelines using Python, SQL, and services like Lambda, S3, and Step Functions to support high-performance analytics platforms.
Design and maintain large-scale data platforms, metadata systems, and semantic models for enterprise clients using Python, SQL, and modern data stack tools.
Builds and deploys generative-AI systems that create culinary content for HelloFresh’s chefs, using Python/SQL and MLOps tools like MLFlow and Prefect.
Build and maintain cloud-native data pipelines and warehouses to power AI/ML models and analytics for a PropTech client, using Python, Spark, SQL, and tools like Snowflake, Airflow, and Kafka.
Build and maintain data pipelines in Snowflake, SQL Server, and PostgreSQL to feed analytics and reporting for an insurer’s underwriting, claims, and policy systems.
Build and maintain scalable data pipelines using Snowflake, Prefect, and Python to support AI-driven investment strategies for institutional clients.
Build and maintain IBM’s Quantum Software data lake, designing scalable pipelines and orchestration workflows to power analytics and insights for quantum computing.
Designs and maintains Snowflake-based data pipelines and ETL workflows using SQL, Python, and orchestration tools like Airflow.
Designs and builds Snowflake-based ETL pipelines and data flows using SQL, Python, and orchestration tools like Airflow or dbt for analytics and reporting.
Build and scale the back-end of a data-science platform that models human behavior for healthcare, insurance, and government clients using Python, FastAPI, AWS, and Kubernetes.
Build and maintain Affirm’s scalable batch-infrastructure platform to run ML, financial, and product workloads reliably on AWS, Kubernetes, and workflow orchestrators like Airflow.
Designs and builds data pipelines, warehouses, and analytics systems using Python, Spark, and cloud platforms like Databricks or Snowflake.
Build and optimize distributed data pipelines using Scala/Java/Python, Spark, Kafka, and Delta Lake/Iceberg, then deploy them on GKE with Helm for AI-driven networking analytics.
Build and maintain DRW’s Unified Data Platform, designing pipelines to ingest trading, research, and back-office data using SQL, Python/Java, and modern batch/streaming tech.
Build and govern data pipelines for a global trading firm, integrating vendor datasets and enabling traders and researchers with reliable, high-quality data products using SQL, Python/Java, and modern streaming/batch tech.
Design and optimize AI data pipelines, feature stores, and real-time inference systems using Python, Spark, and cloud infrastructure to power machine learning models.
Lead a small team to design, build, and scale data pipelines and platforms using Python, SQL, and cloud tools, ensuring reliable data for analytics and ML products.
Builds and maintains CDC pipelines to sync Singapore’s legal data into a Neo4j knowledge graph, ensuring AI models stay current with statutory changes via automated ETL and validation.
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