Senior Data Engineer — United States — LinkedIn — 4489358422

This is a Fully Remote Job

About Our Client:

This organization specializes in optimizing cloud data warehouses for platforms like Snowflake and Databricks to manage compute costs while maintaining query performance. It leverages advanced machine learning techniques to adapt warehouse settings in real time according to each customer's workload, reducing the need for manual adjustments by data teams. The company is venture-backed and operates fully remotely.

About the Opportunity:

The SENIOR DATA ENGINEER is responsible for designing and scaling data pipelines and machine learning infrastructure that support the platform's functionality. This role uses AI tools to enhance productivity and collaborates closely with product and machine learning engineers to transform customer data into actionable models and features. The position plays a critical role in ensuring reliable data processes that drive the platform's impact.

Responsibilities:

• Design and build reliable data pipelines processing large volumes of customer warehouse data

• Develop and maintain machine learning operations infrastructure including feature pipelines, training jobs, deployment, and monitoring

• Ensure data quality and accurate data modeling to support models and customer-facing features

• Utilize AI coding tools effectively, including specification writing, parallel task management, and critical review of output

• Create shared AI workflows, guardrails, and review standards to accelerate team productivity

• Evaluate and recommend new tools and models for team adoption

• Produce architectural documentation detailing designs, tradeoffs, and rationale

• Interpret customer needs to prioritize development efforts

• Mentor engineers on effective use of AI coding tools

Requirements:

• 5+ years of data or software engineering experience, including early-stage startup environments

• Expertise in building and scaling production data pipelines, both batch and streaming, with orchestration tools such as Dagster, Airflow, or Temporal

• Practical experience with machine learning operations, including deployment, monitoring, and retraining of models

• Strong skills in data modeling and maintaining high data quality at scale

• Proficient with AI coding agents and strategies for scaling their use across teams

• Ability to critically assess AI-generated outputs, especially regarding customer data

• Sound judgment to balance simplicity and reliability in shipping solutions

• Proficient in SQL and Python

• Experience with cloud platforms, workflow orchestration, containers, and automated deployment pipelines

• Clear and collaborative communication skills, particularly in writing

• Persistence and adaptability in changing environments

Bonus Points:

• Experience with Snowflake or Databricks

• Hands-on application of machine learning techniques such as time-series forecasting, regression, anomaly detection, or reinforcement learning

• Experience building AI agents, agent tooling, or Model Context Protocol servers

• Knowledge of query optimization or workload analysis

• Working knowledge of Java, Go, or JavaScript

Pay Range and Compensation Package:

• Base salary range is $170,000 to $200,000 for US-based candidates, plus equity

• The role is fully remote within the United States with required work authorization; visa sponsorship is not provided

Benefits & Perks:

• Medical, dental, and vision insurance

• 401(k) retirement program

• Paid time off and paid parental leave

• Home office stipend

• Access to the latest AI tools with freedom to experiment

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

7VA57ntcM is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.