We are looking for a sharp, insurance-domain-aware Data Consultant to join our data engineering team and work exclusively with one of our key insurance clients. This is a dedicated engagement, you will be embedded within the client's data ecosystem, owning pipelines, driving data transformations, and translating complex insurance operations into structured, decision-ready data products.
You will sit at the intersection of insurance operations and data engineering, understanding policy, commissions and incentives and payout/accounting workflows while building the technical infrastructure to make that data reliable, fast, and actionable.
Data Pipeline Engineering
- Design, build, and maintain scalable data pipelines ingesting insurance operational data (policy, supporting datasets such as employee details, CRM activities, training data)
- Develop and optimize ETL/ELT workflows across structured (SQL) and semi-structured (JSON/MongoDB) data sources
- Ensure pipeline reliability, scheduling, monitoring, and alerting with minimal manual intervention
Insurance Domain Data Modelling
- Translate complex incentive structures and payout workflows, including agent commissions, incentives into clean, normalized data models
- Document data dictionaries, schema definitions, and transformation logic for client-facing deliverables
Analytics Enablement
- Prepare clean, analytics-ready datasets for dashboards, actuarial models, and management reporting
- Support ad-hoc analytical requests with SQL queries, MongoDB aggregations, and scripting (Python/JavaScript)
System Integrations
- Integrate the incentive output with downstream systems — accounting/GL platforms, payroll, and HRIS — including journal entry generation (CGST/SGST/IGST handling where applicable) and payout file generation.
- Build and support workflow requirements to fulfill business requirements related to downstream data consumption
Client Engagement
- Act as the primary technical point of contact for data-related queries from the dedicated client
- Communicate clearly with both technical and non-technical insurance stakeholders
- Produce regular status updates, pipeline documentation, and data health reports
A strong understanding of insurance operations is preferred. The ideal candidate will be familiar with:
- Core insurance lines: P&C, Life, Health, or Specialty (at least one in depth)
- Key operational data areas: Incentive management, commission payouts, payout reconciliation, and incentive disbursement
- Working with real-world insurance data from legacy source systems
Who You Are
- When you think about data, you naturally ask 'Do I completely understand each and every data field present in this datasets”' and “How do multiple datasets link together and what would it allow me to answer”
- You are technically hands-on and comfortable writing and debugging code independently
- You can read a business process, identify its data footprint, and model it cleanly
- You communicate complex technical findings to non-technical insurance stakeholders with clarity
- You thrive in a dedicated client model, you build trust, take ownership, and deliver consistently
- You are detail-oriented with a high bar for data accuracy and documentation quality
- You Mentor junior data engineers and consultants on the account; review pipeline code and enforce data quality and auditability standards.
Qualifications
- 2-3 years of experience in data engineering, analytics engineering, or a related data role
- Good to Have: Prior experience in the insurance industry
- Bachelor's or Master's degree in Computer Science, Statistics, Engineering, Mathematics, or a related field
- Strong SQL skills are non-negotiable; MongoDB proficiency is highly preferred
- Experience with Python or JavaScript for data processing; both is a plus
- Excellent written and verbal communication skills in English
- Based in Chennai or willing to relocate, this is an on-site, dedicated engagement role
Nice to Have
- Experience with BI tools (Power BI, Tableau, Looker) for data validation and stakeholder reporting
- Familiarity with cloud data platforms (AWS, GCP, Azure) and data warehousing solutions
- Knowledge of actuarial data workflows or experience supporting actuarial teams
- Certifications in cloud, data engineering, or insurance domain (ACII, AICPCU, etc.)
