Tecton helps companies unlock the full potential of their data for AI applications. The platform streamlines the complex process of preparing and delivering data to models. With Tecton, AI teams accelerate the development of smarter, more impactful AI applications.
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 (talk, blog post) - 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 staff-level engineer on the Batch Compute 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
Responsibilities
- Own and lead large technical domains starting from the problem definition and technical requirements to implementation and maintenance
- Lead multi-engineer projects of strategic importance to Tecton spanning cross-functional teams including product management and other engineering teams
- Drive efforts to improve engineering practices, tooling, and processes along with mentorship for senior engineers
- Develop a deep understanding of the fundamental problems our customers face in building ML systems
- Be a generalist as needed. We’re a small, but growing engineering team and each engineer needs to be versatile
Qualifications
- Experience working in large Python, Java, Kotlin, or Go codebases and running cloud-native Spark systems (e.g. AWS EMR, Databricks, GCP Dataproc)
- Experience in performance tuning of Spark, Ray, Maestro, or Airflow jobs
- Knowledge of data formats such as Parquet, Avro, Arrow, Iceberg, or Delta Lake and object storage (e.g. S3, GCS)
- Expertise with cloud-scale query performance, query optimization, query planning, heuristic query execution techniques, and cost-driven optimizations
- Experience with internals of distributed systems, SQL/NoSQL databases, data lakes, or data warehouses
- Strong communication skills and ability to write detailed technical specifications
- Excitement about coaching and mentorship of junior engineers
- BSc, MS, or PhD in Computer Science or related fields
- 8+ years of experience in building product software systems
- 5+ years of technical leadership experience for a group of engineers
Tecton values diversity and is an equal opportunity employer committed to creating an inclusive environment for all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other applicable legally protected characteristics. If you would like to request any accommodations from the application through to the interview, please contact us at [email protected].
This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
Top Skills
What We Do
Founded by the team that created the Uber Michelangelo platform, Tecton provides an enterprise-ready feature store to make world-class machine learning accessible to every company.
Machine learning creates new opportunities to generate more value than ever before from data. Companies can now build ML-driven applications to automate decisions at machine speed, deliver magical customer experiences, and re-invent business processes.
But ML models will only ever be as good as the data that is fed to them. Today, it’s incredibly hard to build and manage ML data. Most companies don’t have access to the advanced ML data infrastructure that is used by the internet giants. So ML teams spend the majority of their time building custom features and bespoke data pipelines, and most models never make it to production.
We believe that companies need a new kind of data platform built for the unique requirements of ML. Our goal is to enable ML teams to build great features, serve them to production quickly and reliably, and do it at scale. By getting the data layer for ML right, companies can get better models to production faster to drive real business outcomes.
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