Senior AI / Data Engineer

Our client is seeking a Senior AI / Data Engineer to take ownership of building and scaling the data and ML infrastructure that powers their AI‑driven products. This is a hands‑on, high‑impact role for someone who understands that great AI starts with great data engineering . Remote some travel may be required.

What You’ll Do:

Engineering & AI Enablement

• Own the development of trusted AI/ML predictions and forecasts , including feature pipelines, model input/output data flows, and robust data validation frameworks
• Design and implement reliable, scalable, and secure data pipelines that support both analytical and product use cases
• Provide technical leadership and mentorship to data engineers and cross‑functional partners, fostering a culture of engineering excellence

Ecosystem Ownership & Strategy

• Own the architecture and evolution of the data platform to meet performance, scalability, and agility needs
• Implement data governance, quality, and observability best practices , proactively managing data health before issues impact the business
• Optimize cloud data infrastructure for cost, performance, and maintainability, treating the platform as a product—not just a utility

Collaboration & Business Translation

• Partner closely with product managers, engineers, and customer‑facing teams to translate business needs into effective engineering solutions
• Ensure data and ML initiatives are aligned with delivering clear business value and an exceptional customer experience

What You’ll Bring:

Experience:

• 5+ years of experience in data engineering
• 1–2+ years in a senior or lead capacity

Technical Expertise:

• Deep understanding of machine learning models and the ability to articulate trade‑offs (e.g., accuracy vs. interpretability, complexity vs. inference speed)
• Advanced Python skills for complex data structures, automation, and pipeline development
• Strong SQL expertise

ML & MLOps:

• Experience with Scikit‑Learn and similar libraries
• Hands‑on experience building and maintaining feature engineering pipelines
• Strong proficiency with MLOps and orchestration tools such as Airflow, dbt, or Dagster

Modern Data Stack:

• Experience with platforms such as Snowflake, BigQuery, Redshift, or Databricks
• Strong understanding of data modeling, performance optimization, and cloud computing (AWS, GCP, or Azure)

EEO Policy: Allied Resources complies with all Equal Employment Opportunity (EEO) affirmative action laws and regulations. Allied Resources does not discriminate on the basis of age, race, religion, color, sex, national origin, marital status, genetic information, sexual orientation, gender identity and expression, disability, veteran status or other status protected by law