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At Tecton, we solve the complex data problems in production machine learning. Tecton's feature platform makes it simple to activate data for smarter models and predictions, abstracting away the complex engineering to speed up innovation. Tecton's founders developed the first Feature Store when they created Uber's Michelangelo ML platform, and we're now bringing those same capabilities to every organization in the world. Tecton is funded by Sequoia Capital, Andreessen Horowitz, and Kleiner Perkins, along with strategic investments from Snowflake and Databricks. We have a fast-growing team that's distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter. We are building Rift - a new fully managed compute environment that allows data scientists to construct powerful batch and streaming pipelines in Python. Our new environment leverages popular open-source technologies such as Ray, Arrow, and DuckDB. We also have deep integrations with Spark platforms (Databricks, EMR, Dataproc) and data warehouses (e.g. Snowflake, BigQuery, RedShift), along with performant training data pipelines and a workload orchestration platform. As a senior engineer on the Batch Data team, you'll play a critical role in architecting, designing, and scaling the core compute engines and storage architecture used by every Tecton customer. You'll contribute to the performance of our query optimizer, from parsing & optimization to plan selection. Think of this team as the “beating heart” of Tecton. This role is a unique opportunity that combines customer-obsessed product focus with platform and data engineering innovation and helps companies accelerate their path to real-time AI. You will be working in one or more of the following areas to build the next generation of Tecton infrastructure: Distributed compute and resource management, Query optimization and distributed execution, Cross-platform integrations with state-of-the-art data platforms.
