Data Engineer – Claims Data & AI Enablement Senior Consultant II

Allstate Allstate · Insurance · Bangalore, India

Data Engineer supporting the design, development, and delivery of scalable data solutions for claims analytics, reporting, and AI-driven initiatives. The role focuses on making structured and unstructured data available for advanced analytics, reporting, and data science solutions, including emerging AI use cases. Responsibilities include developing data ingestion, transformation, and processing workflows, preparing curated datasets for ML and AI, integrating data from various sources, and applying DevOps practices. The role partners with data scientists and technology teams to support AI use cases and improve data platform needs.

What you'd actually do

  1. Develop and enhance data ingestion, transformation, and processing workflows across batch and transactional environments.
  2. Contribute to solutions that ingest, store, and process structured and unstructured data to support analytics and data science use cases, including select AI-driven applications.
  3. Prepare and deliver curated data sets to support advanced analytics, reporting, and data science initiatives, including machine learning and emerging AI capabilities.
  4. Works within defined work tracks and partners with team members to deliver data solutions aligned to business and analytics needs.
  5. Leverages best practices and receives coaching to support solution development and delivery .

Skills

Required

  • Python
  • SQL
  • Spark or similar frameworks
  • cloud data platforms such as AWS, Azure, or Microsoft Fabric
  • structured and unstructured data processing concepts
  • data modeling
  • relational databases
  • DevOps and CI/CD practices
  • problem-solving
  • collaboration skills

Nice to have

  • 8 or more years of experience
  • claims or insurance data
  • unstructured data pipelines (e.g., text, audio, image processing)
  • orchestration tools such as Airflow or Dagster
  • supporting AI/ML or generative AI initiatives
  • modern data platforms (e.g., Lakehouse, Microsoft Fabric)

What the JD emphasized

  • AI-driven initiatives
  • emerging AI use cases
  • machine learning
  • emerging AI capabilities
  • AI use cases
  • AI and data platform needs

Other signals

  • support AI-driven initiatives
  • emerging AI use cases
  • machine learning
  • emerging AI capabilities
  • evolving AI and data platform needs