Principal Data Engineer - AI
First seen by Alion on Nov 9, 2026.
Job Description for Principal Data Engineer with AI
Cotiviti Hyderabad is looking for a Principal Engineer with AI for one of its product teams. The purpose of this position is to provide technical leadership and guidance to the team, work independently, and build and operate robust, fault-tolerant, and secure data pipelines and platforms that power analytics and AI solutions.
Job Responsibilities:
- Lead the design and development of scalable, fault-tolerant data pipelines and data platform components.
- Drive the technical direction, architecture standards, and engineering practices for the team.
- Design, build, and operate batch and incremental data pipelines using SQL, Python, and Spark on AWS.
- Own the data quality framework and lead root cause analysis of data and pipeline issues.
- Use AI-assisted engineering tools to improve productivity, code quality, testing, and documentation.
- Partner with data scientists and machine learning engineers on the handoff between data engineering and machine learning.
- Build the data foundation for AI use cases, such as curated and governed datasets and pipelines that support LLM solutions.
- Ensure the security and compliance of data pipelines, including the protection of PHI.
Qualifications:
- Master's or Bachelor's degree in Engineering, IT, Computer Science, or related fields.
- 10+ years of hands-on experience in data engineering and SDLC, with deep expertise in SQL and Python.
- Strong hands-on experience with AWS data and DevOps services (S3, Glue, Lambda, EMR, IAM, etc.).
- Experience building production data pipelines with Spark (PySpark) and orchestration tools like Apache Airflow or Databricks.
- Relevant knowledge of AI/ML, including model training, inference, and LLM/Generative AI solutions.
- Hands-on experience using AI tools (Claude Code, GitHub Copilot) to improve engineering productivity.
- Proficiency in APIs, microservices architecture, and CI/CD pipelines.
Skills
Data Engineering, Python, SQL, AWS, Spark, Machine Learning, Artificial Intelligence, Databricks, MLOps, Generative AI