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Senior Data Engineer building and scaling ML-powered data products (OCR, transaction coding, RAG/agentic systems) on a commercial banking platform, using Python, Go, Snowflake, DBT, Kubernetes, and GCP.
The Data Platform Engineer will build and maintain modern data platforms, focusing on pipelines, processing, orchestration, and infrastructure. The role involves working with open-source technologies like Python, SQL, Kubernetes, and various data processing engines to deliver scalable data solutions.
Senior Data Platform Engineer advises clients on modern data platforms, designs scalable architectures, and builds robust open-source solutions with Python/SQL, Spark, Kafka, and Kubernetes. Focuses on governance, performance, and hands-on engineering for enterprise clients.
Data Engineer building and maintaining ETL/ELT pipelines on Azure/AWS using Python, SQL, Databricks/Snowflake/Redshift, Airflow, and dbt in a hybrid London role.
Builds and maintains Box’s data foundation using dbt and BigQuery, designing models, metrics, and pipelines to power analytics and AI-driven workflows.
Rebuilds and operates a US sports-insurance client’s data platform, migrating from legacy ETL to Azure/Snowflake pipelines, productionizing ML scoring, and owning DevOps (IaC, CI/CD, cloud migration).
Data Engineer designing and maintaining ETL/ELT pipelines with SQL, Python/Scala/Java, Airflow/NiFi/Prefect, and relational/NoSQL databases on a cyberdefense project for a large defense company.
Designs and maintains production-grade data pipelines for AI/ML and RAG systems, focusing on ingestion, transformation, and vector search infrastructure (pgvector, Pinecone). Ensures data governance, compliance, and quality for regulated sectors like healthcare and government.
Senior Data Engineer building AI-ready data pipelines, RAG/vector search infrastructure, and data governance solutions using Python, Airflow, Kafka, and vector databases like pgvector and Pinecone.
Builds and maintains data pipelines for a real-time in-game store recommendation engine, sourcing external market signals and serving competitiveness scores via AWS and ClickHouse.
Senior Data Engineer at HPE's Aruba/Networking BU designing and building scalable data pipelines, integrating enterprise data sources (Databricks, IT platforms), and enabling analytics using SQL, Python, orchestration tools, and cloud technologies.
The Senior Data Engineer will design and build scalable data pipelines and analytical layers to support the Global Customer Experience Analytics team. The role involves integrating complex data sources using SQL, Python, and cloud-based orchestration tools to enable data-driven insights.
Mid-level Data Engineer building high-volume data processing pipelines using Redshift, Athena, Iceberg, Spark, and Airflow for Ookla's internet performance data platform.
Senior Data Engineer building and maintaining Snowflake/SQL Server data pipelines, executing batch-to-API migrations, implementing CI/CD and data quality frameworks for a lending/financial services data platform.
Hands-on Quantitative Risk Lead building and deploying production-grade Python microservices for VaR engines, derivatives pricing, and CIRO 5000 regulatory margin models, while managing a small quant team at Wealthsimple.
Manage a team of ML engineers at a fraud detection company, driving innovation in real-time ML fraud models using the Python data stack while staying 30-40% hands-on in the codebase.
Build and own AI features for a construction tech startup, spanning LLM optimization, document processing, and full-stack development to solve real-world problems for professionals.
About Us Savant is transforming how healthcare and life sciences organizations unlock the value trapped in unstructured medical data. Our platform combines cutting-edge large language models (LLMs) with domain-specific…
Build and own AI agent infrastructure and automation systems that integrate LLMs with internal tools and data platforms to streamline marketing operations at scale.
Designs and maintains data infrastructure and pipelines to support AI-driven products, curates high-quality datasets, and collaborates with AI engineers and external data providers.
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