Lead AI Data Engineer

Innorev Technologies Inc; Irving (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Innorev Technologies Inc seeks a Lead AI Data Engineer to design scalable data platforms for AI/ML applications. You will build ETL/ELT pipelines, optimize data solutions on Snowflake/Databricks, and integrate data from multiple sources to support GenAI and LLM initiatives.

You will lead technical teams, ensure data quality and governance, and collaborate with AI/ML engineers and data scientists to deliver production-ready AI solutions. Strong leadership and cloud experience are required.

Qualifications

• 15+ years of experience in data engineering, including technical leadership.
• Strong Python, SQL, Spark, and PySpark programming skills.
• Hands-on experience with Snowflake and/or Databricks.
• Experience with AWS, Azure, or GCP.
• Knowledge of GenAI, LLMs, RAG pipelines, and vector databases.
• Experience with ETL/ELT, data modeling, data lakehouse architecture, and distributed processing.
• Strong leadership, problem-solving, and stakeholder communication skills.

Responsibilities

• Lead the design and development of scalable data pipelines and data platforms for AI/ML applications.
• Build ETL/ELT pipelines using Python, SQL, Spark, and PySpark.
• Design and optimize data solutions using Snowflake, Databricks, and cloud platforms (AWS/Azure/GCP).
• Develop data pipelines to support LLMs, RAG, vector databases, and Generative AI applications.
• Integrate structured and unstructured data from multiple enterprise sources.
• Implement data quality, governance, security, and performance optimization.
• Collaborate with AI/ML engineers, data scientists, and architects to deliver production-ready AI solutions.
• Lead technical teams, conduct code reviews, and establish data engineering best practices.

Skills

Python

SQL

Spark

PySpark

Snowflake

Databricks

AWS/Azure/GCP

GenAI

LLMs

RAG pipelines

Vector databases

ETL/ELT

Data modeling

Data lakehouse

Distributed processing

Tools

Apache Airflow

Kafka

dbt

Job description

We are looking for a Lead AI Data Engineer to design and lead scalable data engineering solutions that support AI, Generative AI, and machine learning applications. The candidate should have strong hands-on experience in data architecture, cloud platforms, data pipelines, and AI/ML data integration.

Key Responsibilities:

• Lead the design and development of scalable data pipelines and data platforms for AI/ML applications.
• Build ETL/ELT pipelines using Python, SQL, Spark, and PySpark.
• Design and optimize data solutions using Snowflake, Databricks, and cloud platforms (AWS/Azure/GCP).
• Develop data pipelines to support LLMs, RAG, vector databases, and Generative AI applications.
• Integrate structured and unstructured data from multiple enterprise sources.
• Implement data quality, governance, security, and performance optimization.
• Collaborate with AI/ML engineers, data scientists, and architects to deliver production-ready AI solutions.
• Lead technical teams, conduct code reviews, and establish data engineering best practices.

Required Skills:

• 15+ years of experience in data engineering, including technical leadership.
• Strong Python, SQL, Spark, and PySpark programming skills.
• Hands-on experience with Snowflake and/or Databricks.
• Experience with AWS, Azure, or GCP.
• Knowledge of GenAI, LLMs, RAG pipelines, and vector databases.
• Experience with ETL/ELT, data modeling, data lakehouse architecture, and distributed processing.
• Strong leadership, problem-solving, and stakeholder communication skills.

Preferred Skills:

• Experience with Apache Airflow, Kafka, dbt, and orchestration frameworks.
• Familiarity with ML pipelines, feature engineering, and MLOps.
• Experience deploying production-scale AI and data platforms.