AI-Enabled Data Engineer

AI-Enabled Data Engineer

AI/ML-driven insights

Key Responsibilities

• Design, develop, and optimize

  complex SQL queries

  across Teradata, Snowflake, and Databricks platforms.
• Build and maintain

  scalable, resilient data pipelines and ETL/ELT workflows

  using Azure-native services.
• Implement data ingestion, transformation, and orchestration using

  Azure Data Factory

  , Databricks notebooks, and related tools.
• Collaborate with

  AI/ML teams

  to integrate machine learning models into production data pipelines and analytics workflows.
• Ensure

  data quality, accuracy, governance, and security

  across cloud and hybrid data platforms.
• Monitor, troubleshoot, and tune performance of data pipelines, queries, and large-scale data processing jobs.
• Support data consumption for reporting, analytics, and AI use cases by enabling efficient data access patterns.
• Document

  data architectures, workflows, standards, and best practices

  .
• Participate in Agile ceremonies and contribute to continuous improvement initiatives.

Required Skills & Qualifications

• 5+ years

  of experience in data engineering, data analytics, or related roles.
• Strong proficiency in

  SQL

  , with hands-on experience in

  Teradata, Snowflake, and Databricks

  .
• Solid experience with

  Azure cloud services

  , including:
• Azure Data Factory
• Azure Synapse Analytics
• Azure Blob Storage / Data Lake Storage
• Azure DevOps

• Hands-on experience with

  Apache Spark

  using Databricks for large-scale data processing.
• Exposure to

  AI/ML workflows

  , including data preparation and model integration into data platforms.
• Strong understanding of

  data modeling, performance tuning, and query optimization

  .
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Proficiency in

  Python and/or Scala

  for data engineering and AI integration use cases.
• Experience with

  CI/CD pipelines

  , version control, and

  infrastructure-as-code

  in Azure environments.
• Knowledge of

  data governance frameworks

  , metadata management, and compliance standards such as

  GDPR or HIPAA

  .
• Relevant

  certifications

  in Azure, Snowflake, or Databricks.
• Prior experience working with large-scale enterprise or cloud-native data platforms.

  Role & responsibilities