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Owns Kestra’s data orchestration product, defining features for data pipelines, integrations with dbt/Airbyte/Snowflake, and migrations from Airflow—releasing value quickly without heavy process.
Design and maintain cloud data pipelines and datasets to track cloud costs, usage, and performance for engineering and finance teams using AWS, Snowflake, Python, and SQL.
Lead the design and deployment of scalable AI/GenAI solutions and petabyte-scale data platforms, from ingestion to production, using cloud, Spark, Databricks, and Snowflake.
Build and maintain Gropyus’s data ingestion, transformation, and storage pipelines using Python, Kubernetes, and BigQuery to support planning, construction, and operations.
Lead a team that builds and maintains Samsara’s petabyte-scale data lake and analytics platform, using AWS, Spark, and modern data-lake formats to power IoT-driven insights for industries like transportation and manufacturing.
Build and deploy ML systems that power healthcare workflows: speech-to-text, LLM note-taking, and chat-based clinical assistants in a cloud-native stack.
Principal Data Engineer designs and scales enterprise-grade data infrastructure and real-time pipelines for AI-driven product analytics and autonomous agents at Salesforce’s AgentExchange.
Build and maintain scalable data pipelines and AI-ready platforms for next-gen AI products, transforming raw data into trusted assets for analytics and machine learning.
Develops AI-driven geospatial models to analyze satellite imagery for vegetation risk assessment in energy grids, improving wildfire prevention and outage reduction using Python, PyTorch, and geospatial libraries like GDAL and GeoPandas.
Build and maintain the ML platform that deploys, monitors, and scales AI models powering Hadrian’s autonomous factories, using MLflow, Dagster, EKS, and FastAPI.
Architect and lead enterprise-scale data platforms, MDM, and agentic AI integrations (RAG, LLM workflows) in cloud-native environments, while setting engineering standards and mentoring teams.
Architect and lead enterprise-scale data platforms, MDM, and agentic AI systems, building scalable pipelines and trusted data foundations for analytics and AI-driven applications.
Builds and maintains the software/data infrastructure for a healthcare AI research project, focusing on developing multi-modal foundation models for blood analysis using anonymized clinical data. Core tech: Python, SQL, distributed systems, Kubernetes, databases (PostgreSQL, DuckDB), data pipelines (Airflow, dbt), and security-by-design principles.
Development and optimization of large-scale data processing workflows using Apache Spark, PySpark, and SQL Building and enhancing multi-stage ETL pipelines with idempotency and failure recovery Implementation and…
Lead a team to build and maintain Samsara’s petabyte-scale data platform, driving AI transformation and scalable infrastructure for IoT-driven operations across industries like agriculture, construction, and transportation.
Build and own Minerva’s consumer-data products, transforming raw signals into trusted attributes and scalable pipelines that power AI agents, APIs, and enterprise marketing campaigns.
Builds production-grade software applications integrating data pipelines and ML models for internal decision-support tools and operational dashboards, collaborating with data/ML engineers to create scalable, user-friendly solutions.
Build and maintain the ML platform that deploys, monitors, and scales AI models for Hadrian’s autonomous factories, using MLflow, Dagster, EKS, and FastAPI.
Build and maintain the data backbone for autonomous factories, integrating machine signals, quality events, and operational data into reliable datasets for ML, analytics, and scheduling using Python, SQL, Kafka, Snowflake, and Dagster.
Lead the architecture and scaling of Foodsmart’s data platform, owning pipelines, dbt, and warehouse infrastructure to deliver reliable, HIPAA-compliant insights for analytics, BI, and AI tools across 2.2M members.
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