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The Assistant Vice President will lead the design and operation of modern data platform capabilities, including lakehouse architecture and data pipelines, to support investment management. The role involves hands-on engineering with Spark, Python, and SQL while providing technical leadership to a team.
Senior Data Engineer builds and maintains scalable ETL/ELT pipelines and lakehouse datasets to power analytics, ML, and business applications at Hertz.
Senior Data Scientist designing and deploying ML models for real-time bidding, audience targeting, and campaign optimization on Amadeus's travel advertising platform, using Python, SQL, TensorFlow, and GCP.
Design and implement scalable data architectures and ETL pipelines using Java, Spark, and cloud tools to support risk and regulatory reporting in a large bank.
Data Architect at Mount Sinai Health System designing and implementing Big Data/ETL/Data Warehousing solutions using Azure, Databricks, SQL/NoSQL databases, Python, and big data stacks like Hadoop, Spark, and Kafka in a hybrid arrangement.
Builds and maintains scalable digital identity platforms for ING’s global fintech services, focusing on JVM-based microservices, Kafka, and cloud-native tooling like OpenShift.
Senior Data Engineer designing and building scalable Azure Databricks-based data pipelines, ETL processes, and lakehouse architectures using Python, SQL, Apache Spark, and Delta Lake at a law firm.
The Principal Software Engineer will architect end-to-end data solutions, lead cloud migrations, and design scalable data pipelines using big data and GenAI technologies. This role involves mentoring junior engineers and collaborating with stakeholders to implement data-intensive applications and infrastructure.
The Lead Software Engineer will architect and lead the development of scalable data engineering infrastructure, focusing on cloud migrations, data modeling, and real-time data pipelines. The role requires extensive experience with big data technologies, cloud platforms like AWS/Azure/GCP, and leading technical teams in a product-based environment.
The Staff Data Scientist will lead the development of next-generation AI systems and autonomous agents to improve Walmart's global operations. The role involves architecting end-to-end ML pipelines, mentoring senior talent, and deploying production-grade AI solutions using technologies like PyTorch, LangChain, and cloud-based ML platforms.
The Data Engineer will design, develop, and maintain scalable data pipelines, warehouses, and cloud-based platforms to support business intelligence and analytics. The role involves working with technologies like Python, SQL, Spark, and cloud infrastructure to ensure data quality and reliability within an automotive electronics environment.
Builds and maintains AI-driven data products for travel platforms, designing scalable cloud-native systems and pipelines to power analytics, reporting, and personalized travel experiences.
Build and maintain high-volume healthcare data systems that process millions of transactions daily, using languages like C# and Java, while integrating responsible AI tools to improve reliability and patient outcomes.
Develops AI features and cloud-native applications for government intelligence systems, integrating data streams and applying DevSecOps practices in an agile environment.
Senior AI software engineer building generative-AI features for government systems in Springfield, VA, using Python/Java/Scala, cloud-native stacks, and DevSecOps practices.
Builds and maintains scalable data pipelines for Blackline Safety’s IoT-enabled safety ecosystem, processing real-time and batch datasets from global devices to ensure accuracy, security, and timely delivery for product and engineering teams.
Build and own Snowflake’s distributed billing platform, metering AI product usage and shaping pricing models while collaborating with finance, product, and AI teams.
Build and deploy ML systems for healthcare analytics, automating model lifecycle management, CI/CD, and cloud infrastructure to improve patient care and operational efficiency.
Leads user understanding for Netflix’s ad-supported tier by building ML systems that analyze multimodal signals (content, viewing behavior) to improve ad targeting, ranking, and bidding. Shapes data strategy and partners across Ads ML teams.
Oversees data infrastructure, pipelines, and governance for a major financial institution, ensuring secure, scalable, and efficient data collection, storage, and analysis to drive business insights and operational efficiency.
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