Role Overview
We are seeking a
Data Engineer with Generative AI expertise
to join our Insurance Analytics team in Gurgaon. The role requires a blend of
data engineering, cloud, and GenAI skills
, with a focus on building robust data pipelines and deploying AI-driven solutions to solve complex insurance business challenges.This is a
hands-on engineering role
where you will work with insurance clients, business stakeholders, and data science teams to design, implement, and optimize data/GenAI solutions.
Key Responsibilities
- Data Engineering & Pipelines
- Design, build, and maintain scalable ETL/ELT pipelines using modern data platforms (Azure, AWS, GCP).
- Integrate structured and unstructured insurance data sources (policy, claims, underwriting, actuarial, customer data).
- Optimize data pipelines for performance, scalability, and cost efficiency.
- Generative AI Enablement
- Collaborate with data scientists and solution architects to embed GenAI models (LLMs, copilots, prompt engineering) into insurance workflows.
- Develop connectors, APIs, and middleware to integrate GenAI solutions with enterprise systems.
- Fine-tune and customize foundation models for insurance-specific use cases (e.g., claim notes summarization, underwriting automation, agent assistance).
- Cloud & Architecture
- Build cloud-native data platforms leveraging Databricks, Azure Synapse, AWS Redshift, or GCP BigQuery.
- Ensure compliance with insurance data governance, privacy, and regulatory requirements (HIPAA, GDPR, IRDAI).
- Collaboration & Delivery
- Partner with BI/reporting teams, actuaries, and insurance SMEs to ensure data availability for analytics & AI use cases.
- Work in agile project teams, participating in design workshops, sprint planning, and code reviews.
- Provide technical guidance and training to junior engineers.
Required Skills & Experience
- Education: Bachelor’s/Master’s in Computer Science, Data Engineering, or related fields.
- Experience: 4–8 years in data engineering, with at least 1–2 years hands-on in GenAI/LLM integration.
- Technical Skills:
- Strong SQL, Python, PySpark/Scala.
- Data platforms: Databricks, Snowflake, Synapse, BigQuery.
- Cloud: Azure (preferred), AWS, or GCP.
- GenAI/AI: OpenAI, Azure OpenAI, Hugging Face, LangChain, RAG frameworks.
- Data integration: APIs, REST, Kafka, Delta Lake.
- CI/CD & DevOps tools (Git, Jenkins, Terraform).
- Soft Skills:
- Strong problem-solving and analytical thinking.
- Ability to translate business requirements into technical solutions.
- Excellent communication skills to work with cross-functional teams and insurance clients.
Preferred / Nice-to-Have
- Prior experience in insurance or financial services analytics.
- Exposure to prompt engineering, fine-tuning LLMs, and building copilots.
- Familiarity with BI/Visualization tools (Power BI, Tableau).
Knowledge of
data security, compliance, and audit frameworks
in insurance.
