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Staff Data Engineer designs and owns Vandebron’s lakehouse, warehouse, and MLOps platform, setting engineering standards and driving scalable data infrastructure for green-energy analytics.
Lead the design and scaling of a lakehouse architecture and MLOps pipeline for Vandebron’s data platform, mentoring engineers and enforcing data governance.
Architect and build large-scale cloud-native data pipelines for cross-device identity resolution using Python and SQL in a media intelligence company.
Build and maintain a self-serve data platform for a large classifieds marketplace, owning batch and streaming pipelines, lake management, and APIs that power analytics and ML workloads using Databricks, AWS, Spark, Python, Kafka, and Airflow.
Lead the design and scaling of a modern data platform, building self-service tools and enabling AI initiatives in a cloud environment using Databricks, Spark, and infrastructure-as-code.
Build and scale backend services for a data and AI infrastructure platform using Java/Scala/C++.
Designs and builds large-scale data pipelines for AI systems, ensuring robust, reproducible, and cost-efficient data infrastructure for research-to-production transitions.
Lead the design and operation of large-scale data pipelines for AI research and production, focusing on multimodal and spatial data to enable frontier-model training and deployment.
Build and scale real-time data infrastructure for a high-throughput crypto social network, designing pipelines, analytics systems, and storage solutions in Python/SQL with Spark, Kafka, and ClickHouse.
Build and operate a cloud-native data platform on Snowflake and public cloud, owning provisioning, ingestion pipelines, transformations, governance, and cost-efficient scaling for analytics across the travel-tech company.
Build and maintain large-scale backend services and data pipelines for paid marketing systems, integrating ad platforms like Google Ads and Meta to optimize global travel ad campaigns.
Lead the design and implementation of scalable big-data and cloud platforms, building robust data-intensive applications and frameworks.
Build and own the data foundation for Zendesk’s product analytics, designing scalable pipelines, semantic layers, and standards to power data-driven decisions and AI-assisted workflows.
Lead the data team and architect scalable pipelines for Yuno’s cross-border payments platform, ensuring data quality, observability, and governance while mentoring engineers.
Build and scale Qualifyze’s data platform, owning pipelines, modeling, and quality with SQL, Python, dbt, and orchestration tools while mentoring engineers.
Build and scale Spotify’s data platform to analyze Premium subscriber behavior, retention, and engagement, enabling analytics, ML, and product decisions for 200M+ users.
Build and own end-to-end data pipelines in Snowflake and AWS, modeling billions of records into bronze, silver, and gold layers to power business insights and AI agents.
Build and maintain AI/ML data pipelines to power insights and models for a company focused on solving complex problems.
Designs and builds backend systems for a data and AI platform, leads technical projects, and mentors engineers to ensure high performance and reliability.
Leads the design and implementation of scalable backend services for BlackLine's data platform, building integrations with ERP, banking, payments, tax, and subledger systems while mentoring engineers.
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