Senior AI/Data Engineer

United StatesRemoteFull-timesenior

Data ScienceOtherData EngineeringAi Data Engineer

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Quick Summary

Key Responsibilities

AI/ML ownership: Build trusted AI/ML predictions and forecasts via feature pipelines, model input/output data flows, and robust data validation frameworks.

Technical Tools

Data ScienceOtherData EngineeringAi Data Engineer

We’re looking for a customer-centric Senior AI/Data Engineer to build and scale data systems that drive our “decision intelligence” products. You’ll work at the intersection of data engineering, product development, and AI/ML enablement—designing systems that empower customer-facing data products. This role requires not only deep technical expertise but also a strategic mindset, strong communication skills, and a high sense of ownership over how data supports the business. You will collaborate across teams to ensure data is a true product enabler.

WHAT YOU'LL DO:

AI/ML ownership: Build trusted AI/ML predictions and forecasts via feature pipelines, model input/output data flows, and robust data validation frameworks.

Pipeline Design: Design and implement reliable, scalable, and secure data pipelines that serve analytical and product use cases.

Leadership: Provide technical leadership and mentorship to other data engineers and cross-functional collaborators, fostering a culture of engineering excellence.

Architecture & Evolution: Own the architecture and evolution of our data platform, ensuring it meets the performance, scalability, and agility needs of our growing business.

Governance & Observability: Implement data governance, quality, and observability best practices to ensure trustworthy insights, proactively managing data health before it impacts the business.

Infrastructure Optimization: Optimize cloud data infrastructure for cost, performance, and maintainability, treating the platform as a product rather than just a utility.

Cross-Functional Partnership: Collaborate closely with product managers, engineers, and customer stakeholders to understand context and needs, and help translate them into engineering solutions.

Customer-Centricity: Ensure engineering efforts are aligned with delivering clear business value and enhancing the customer experience.

The ML Enabler: You are a Data Engineer who loves the complexity of AI. You understand that a model is only as good as the pipeline feeding it, and you take pride in building the infrastructure that brings AI to life.

The Product-Minded Architect: You don’t just move data from A to B; you build systems with the end-user in mind. You prioritize "Time to Insight" and usability as much as you prioritize code efficiency.

The Strategic Owner: You are comfortable working in an environment where you are expected to identify problems and fix them without waiting for a ticket. You view the data ecosystem as your product.

We know that great talent comes from many backgrounds. If you are a builder who cares about the "why" behind the code, we want to hear from you!

Experience: 5+ years of experience in data engineering, with 1–2+ years in a senior or lead capacity.

Deep Technical Expertise: You possess a profound understanding of ML models and can articulate the trade-offs between different architectures (e.g., complexity vs. inference speed, accuracy vs. interpretability) to ensure the right tool is selected for the job.

Coding: "Ninja-level" proficiency in Python for complex data structures and automation, alongside strong SQL expertise.

ML Frameworks: Strong familiarity with Scikit-Learn and similar libraries, with specific experience building and maintaining associated feature engineering pipelines.

Ops & Orchestration: High proficiency in MLOps practices and orchestration tools (e.g., Airflow, dbt, Dagster) to manage model lifecycles and data dependencies.

Modern Data Stack: Solid experience with modern data platforms (e.g., Snowflake, BigQuery, Redshift, or Databricks).

Cloud & Modeling: Strong understanding of data modeling, performance optimization, and cloud computing (AWS, GCP, or Azure).

Communication: Excellent communication and collaboration skills, with a proven ability to work effectively across technical and non-technical teams.

Listing Details

Posted: February 17, 2026
First seen: March 26, 2026
Last seen: April 22, 2026

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Days active: 26
Repost count: 0
Trust Level: 51%
Scored at: April 22, 2026

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Workwave

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WorkWave provides cloud-based software and fintech solutions for field service businesses, helping them manage operations, sales, and customer interactions. The company serves industries like pest control, lawn care, and cleaning.

Employees

750

Founded

1984

Domain

workwave.com

Jobs

View 15 jobs

View company profile

Salary

USD 160000–180000

per year