> Markdown version of [/jobs/ext/2750277-ml-data-platform-engineer](https://www.wearedevelopers.com/jobs/ext/2750277-ml-data-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML Data Platform Engineer - **Company:** PARSLEY ENTERPRISES, INC. - **Location:** New York, NY, United States - **Salary:** $175,000.0 - $245,000.0 - **Contract:** Temporary to permanent - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Information Engineering, Data Files, Data Infrastructure, Data Systems, Software Debugging, Python (Programming Language), Machine Learning, Scientific Computating, SQL Databases, Data Streaming, Databricks - **Published:** September 6, 2026 - **Apply:** https://www.careerjet.com/jobad/usf9dd015140f64b96d0485a9e3c5eee48 ## About the Role You May Be A Fit If - You enjoy making difficult real-world data useful, not merely moving it between systems. - You understand how warehouse or streaming data becomes training, evaluation, and product data. - You care about temporal correctness, reproducibility, leakage, lineage, and source rights. - You can design practical systems without reaching immediately for a large-company platform. - You are comfortable debugging incomplete APIs, changing schemas, and surprising data behavior. - You communicate clearly with researchers, product engineers, and customer-facing teammates. - You want substantial ownership on a small team and can make progress without a mature data organization around you. Helpful Background - Strong Python and SQL experience. - Experience with data engineering, ML data systems, dataset engineering, platform engineering, or high-quality analytics engineering. - Experience with object storage, warehouses, streaming or workflow systems, columnar formats, APIs, and data-quality tooling. - Experience preparing data for model training, evaluation, or scientific computing. - Familiarity with time-series, geospatial, weather, market, event, or other temporally sensitive data is useful. - Startup or small-team experience is helpful, but evidence of unusually strong ownership matters more than a particular company background. ## Description We are looking for an ML Data Platform Engineer to make the data behind our models and products dependable, understandable, and easy to use. This role sits where data engineering meets machine learning. You will turn messy, changing real-world sources into durable datasets and interfaces that researchers, product engineers, and customer-facing technical teams can trust. The goal is not to build a large platform for its own sake. It is to make each new model, product surface, and authorized data source faster to bring online without compromising correctness. What You Will Own - Build and improve ingestion, backfill, validation, and observability for high-volume, time-dependent data. - Define clear data contracts and point-in-time semantics for model training, evaluation, and product use. - Create reusable workflows for bringing new public and customer-authorized sources into the system. - Build quality, lineage, freshness, and access controls that make data trustworthy in repeated use. - Develop efficient datasets and query interfaces for machine-learning and product workloads. - Diagnose whether failures originate in source data, transformations, model inputs, or serving systems. - Work closely with research and product engineers so data requirements become reliable software, not recurring manual projects. - Exercise judgment about which abstractions should become durable infrastructure and which should remain purpose-built. First 90 Days - 30 days: Understand the data lifecycle behind Ask The Grid and our ML work; identify the most consequential reliability and usability gaps. - 60 days: Ship a reusable ingestion, backfill, validation, or dataset primitive used in active product or research work. - 90 days: Own a dependable end-to-end data workflow, with documented contracts, quality checks, and clear operational visibility., Position Title: Data Platform Engineer Databricks Location Seattle / NYC (hybrid work) Responsibilities Design, build, and enhance platform capabilities within Databricks an… + 16 hours ago + Apply easily ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Introduction to TXT](https://www.wearedevelopers.com/videos/30-introduction-to-txt) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)