Senior Data Engineer (AI)

Allied Resources Technical Consultants is seeking a customer-centric Senior AI/Data Engineer to help build and scale advanced data systems that power decision intelligence and customer-facing data products. The role involves designing scalable data solutions, optimizing cloud infrastructure, and leading the architecture of modern data platforms, while collaborating with cross-functional teams to support business growth.

Responsibilities:

• Design and implement scalable, secure, and reliable data pipelines supporting analytics, AI/ML, and customer-facing product initiatives
• Build and maintain feature engineering pipelines, model input/output workflows, and data validation frameworks to support AI/ML forecasting and predictive analytics
• Lead the architecture and evolution of modern cloud-based data platforms with a focus on scalability, performance, and maintainability
• Establish and improve data governance, observability, and quality standards to ensure trusted and actionable business insights
• Optimize cloud infrastructure and modern data stack environments including Snowflake, Databricks, Redshift, or BigQuery
• Collaborate closely with product managers, engineers, and business stakeholders to translate business needs into scalable technical solutions
• Provide technical leadership and mentorship to engineering teams while promoting engineering best practices and innovation
• Drive a product-focused engineering mindset prioritizing usability, efficiency, and “time to insight” for end users

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related technical discipline preferred
• 5+ years of experience in data engineering with at least 1–2 years in a senior or lead-level capacity
• Advanced Python programming expertise for complex data processing, automation, and scalable engineering solutions
• Strong SQL expertise and experience working with large-scale structured and unstructured datasets
• Hands-on experience with machine learning frameworks such as Scikit-Learn and associated feature engineering pipelines
• Strong experience with orchestration and MLOps tools including Airflow, dbt, or Dagster
• Experience working with modern cloud platforms including AWS, Azure, or GCP
• Strong understanding of data modeling, cloud architecture, performance optimization, and scalable system design
• Excellent communication and collaboration skills with the ability to work across both technical and non-technical teams
• Proven ability to operate in fast-paced environments with strong ownership and problem-solving capabilities