Senior Data AI Engineer

KADIT Innovations; Dallas, Northern (TX, KY); Hybrid; USD 120,000 - 170,000; Full time

Job summary

KADIT Innovations is hiring for a data engineering role focused on building scalable data pipelines and AI/ML solutions on Google Cloud Platform. You will work with data scientists and product teams to translate business needs into robust data systems.

The position emphasizes performance, cost optimization, and data quality across large-scale data warehouses, with opportunities to mentor junior engineers and shape architecture decisions.

Qualifications

• 5–8 years of Data Engineering experience.
• Strong hands-on experience with GCP Data Platform and BigQuery.
• 2–3 years of practical AI/ML experience.
• Proficiency in Python and SQL.
• Experience with ETL/ELT pipelines and large-scale data processing.
• Familiarity with ML frameworks and MLOps practices.

Responsibilities

• Design, develop, and maintain scalable, reliable, and cost-efficient data pipelines on GCP.
• Architect and optimize large-scale data warehouses and analytical solutions.
• Build and operationalize end-to-end AI/ML solutions from data prep to deployment.
• Collaborate with data scientists and stakeholders to translate requirements.
• Implement data governance, quality, and security across the platform.
• Develop CI/CD pipelines for data and ML workflows.

Skills

Data Engineering

BigQuery

AI/ML experience

Python

SQL

ETL/ELT pipelines

ML frameworks

System design

Problem solving

Education

Bachelor’s or Master’s in CS/IT/Data Science

Tools

Terraform

Airflow/Composer

Spark

Pub/Sub

Kubernetes

Vertex AI

Job description

• Design, develop, and maintain scalable, reliable, and cost-efficient data pipelines and data platforms on GCP (BigQuery, Dataflow, Cloud Storage, Pub/Sub, Composer, Dataproc, etc.)


• Architect and optimize large-scale data warehouses and analytical solutions using BigQuery, focusing on performance, cost optimization, and data quality.


• Build and operationalize end-to-end AI/ML solutions – from data preparation and feature engineering to model training, evaluation, deployment, and monitoring.


• Collaborate with data scientists, product teams, and business stakeholders to translate business requirements into robust data and AI solutions.


• Implement best practices for data governance, data quality, security, and compliance across the data platform.


• Develop CI/CD pipelines for data and ML workflows (using tools like Cloud Build, Vertex AI Pipelines, Terraform, etc.).


• Monitor, troubleshoot, and continuously improve data pipelines and AI model performance in production.


• Mentor junior engineers and contribute to technical decision-making and architecture reviews.


• Stay updated with the latest GCP services, AI/ML advancements, and industry best practices, and proactively recommend improvements.

Required Skills

• 5–8 years of overall experience in Data Engineering


• Strong hands-on experience with GCP Data Platform and BigQuery


• 2–3 years of practical AI/ML experience (must have)


• Proficiency in Python and SQL.


• Experience with ETL/ELT pipelines, data modeling, and large-scale data processing


• Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and MLOps practices


• Strong problem-solving and system design skills.

Nice to Have Skills

• Experience with Vertex AI, AutoML, or other GCP AI/ML services


• Knowledge of Apache Spark, Airflow/Composer, Kafka/Pub/Sub


• Experience with Infrastructure as Code (Terraform / Deployment Manager)


• Familiarity with containerization (Docker, Kubernetes/GKE)


• Exposure to real-time streaming pipelines and event-driven architectures


• Experience in building RAG systems, LLM applications, or Generative AI solutions


• Previous experience in mentoring or leading small technical teams


• Certifications: Google Cloud Professional Data Engineer / Machine Learning Engineer

Educational Requirements

1. Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, or a related field.


2. Equivalent practical experience will also be considered.