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.

• 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
• 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

• 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

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

• 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

• 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

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

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