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Lead the architecture of a cloud-native B2B SaaS marketing decision platform, designing scalable microservices, AI integrations, and multi-tenant systems on AWS.
Lead the build-out of Databricks’ internal agentic AI platform, redefining the SDLC and replacing legacy SaaS with scalable, in-house AI tools for thousands of employees.
Pre-sales Solutions Architect driving enterprise adoption of Databricks’ data and AI platform for retail, travel, and hospitality clients, designing technical strategies and mentoring teams.
Build and deploy ML models to optimize Databricks’ distributed infrastructure, improving performance and cost efficiency for serverless compute products.
Designs and maintains cloud-based data pipelines and lakes on Databricks/Azure, building scalable ETL/ELT workflows and governance for enterprise analytics and AI solutions.
Sr. Data Infrastructure & Quality Engineer Location: San Francisco, CA Department: Autonomy At Ouster, we are pioneering the future of Physical AI. Our advanced vision algorithms and cutting-edge sensor hardware…
Build end-to-end BI solutions on Microsoft Fabric, from data ingestion to Power BI dashboards, to deliver actionable insights for global healthcare teams.
Build and optimize scalable data pipelines and governed lakehouse platforms using Databricks, Spark, and AWS to support analytics and AI in a regulated biotech environment.
Lead a team to design and deliver scalable data pipelines and platforms for analytics and AI use cases at Mastercard, using SQL, Python, and Databricks.
Design and build scalable cloud-native data pipelines and platforms (batch/streaming) using Python, Spark, Kafka, and cloud data warehouses to power analytics and ML across global telco markets.
Lead a team of 8–15 engineers to design, build, and optimize cloud-based data pipelines and lakehouse architectures using Python, PySpark, Databricks, and cloud platforms like Azure/AWS/GCP.
Designs and maintains scalable data pipelines and platforms to power analytics and reporting across a global healthcare company using cloud technologies and ETL/ELT processes.
Lead a team of data engineers building and operating the data platforms that power Grata’s private-market dealmaking platform, using Python, SQL, Spark/Databricks, and AWS.
Senior AWS data engineer building scalable healthcare data platforms using EMR, Glue, S3, and Redshift to power global health informatics solutions.
Design and build AI-ready data pipelines and products that power retrieval-augmented AI systems, ensuring data quality, governance, and secure access for AI models.
Build and maintain Greystar’s Databricks-native data platform on Azure, administering Unity Catalog, optimizing Spark jobs, and enforcing medallion architecture standards for reliable, cost-efficient enterprise analytics.
Build and optimize Microsoft Fabric lakehouse pipelines and PySpark transformations, then deliver Power BI reports for a US renal-care analytics platform.
Design and lead a cloud-based data architecture on GCP for regulatory reporting, using Java, Kafka, Spark/Flink, and BigQuery to build scalable event-driven and batch pipelines.
Build and maintain scalable data pipelines, ETL workflows, and serverless services on Google Cloud Platform using Python, BigQuery, Pub/Sub, and Cloud Run.
Leads engineering teams to design and deliver cloud-native financial platforms, driving cross-product collaboration and aligning tech strategy with JP Morgan Chase’s fintech goals.
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