Data Strategy & Enrichment Associate

: Data Strategy and Enrichment Associate/Lead

Role Overview

We are looking for an experienced professional to own and drive the Customer 360 (C360) and Vehicle 360 (V360) platforms. The role requires a strong blend of data engineering, data warehousing, data enrichment, data procurement, and stakeholder consulting. The candidate will be responsible for building and scaling comprehensive customer and vehicle intelligence platforms by integrating multiple internal and external data sources and enabling business teams with actionable insights.

Experience: 6–8 Years

Location: Gurgaon

Department: AutoIQ

Key Responsibilities

Customer 360 & Vehicle 360 Ownership

• Own the roadmap, development, and enhancement of the C360 and V360 platforms.
• Build and maintain unified customer and vehicle intelligence layers by integrating multiple internal and external data sources.
• Define data models, enrichment strategies, identity resolution frameworks, and quality standards to improve customer and vehicle data coverage and accuracy.
• Identify and onboard new customer- and vehicle-related data sources to strengthen the C360 and V360 ecosystems.
• Partner with business teams to identify new use cases and data opportunities.

Data Warehousing & Engineering

• Design and manage scalable data warehouse solutions.
• Develop and optimize ETL/ELT pipelines for structured and semi-structured data.
• Ensure data quality, governance, lineage, and monitoring across the ecosystem.
• Work with large-scale datasets in cloud-based data platforms.

• Identify, evaluate, and onboard external data providers and open-source datasets.
• Drive integration of customer and vehicle-related datasets including demographics, employment, financial behavior, registration, ownership, insurance, service history, valuation, telematics, and alternate data sources.
• Assess data vendors for quality, coverage, compliance, and business value.
• Develop enrichment frameworks to maximize customer and vehicle intelligence and business utility.

Data Science

• Collaborate with Data Science teams to support feature engineering and model development
• Support development of risk, fraud, valuation, collections, marketing, cross-sell, customer lifecycle, and portfolio management use cases.
• Define KPIs and measure the impact of data products and enrichments.

Stakeholder Consulting

• Work closely with Product, Risk, Marketing, Collections, Operations, and Leadership teams.
• Gather requirements and translate them into scalable data solutions.
• Present insights, recommendations, and project updates to senior stakeholders.
• Drive cross-functional initiatives involving business, technology, and external partners.

Required Skills

Technical

• Strong SQL expertise with experience handling large datasets.
• Advanced Python programming for data processing and automation.
• Strong understanding of data warehousing concepts and dimensional modeling.
• Experience building and managing ETL/ELT pipelines.
• Experience with Snowflake, Databricks, BigQuery, Redshift, or similar platforms.
• Knowledge of data quality, governance, metadata management, and master data management concepts.

Data & Enrichment

• Strong understanding of data enrichment, entity resolution, and third-party data integration.
• Working knowledge of machine learning and feature engineering concepts.
• Experience with large-scale data enrichment and insight generation.
• Familiarity with reporting and visualization tools.

Consulting & Business

• Strong stakeholder management and communication skills.
• Ability to convert business requirements into technical solutions.
• Experience managing end-to-end data initiatives and vendor relationships.
• Strong problem-solving, prioritization, and project management capabilities.

Preferred Qualifications

• Experience working with customer, mobility, automotive, insurance, lending, fintech, or consumer data ecosystems.
• Exposure to customer identity resolution, demographics, employment, financial behavior, vehicle registration, ownership, insurance, service history, valuation, telematics, or mobility datasets.
• Experience evaluating and onboarding external data providers.
• Understanding of data privacy, compliance, consent management, and data-sharing frameworks.

Success Metrics

• Increased coverage, quality, and depth of the C360 and V360 platforms.
• Faster onboarding and integration of new customer and vehicle data sources.
• Higher adoption of C360 and V360 datasets across business functions.
• Improved reliability, governance, and accessibility of customer and vehicle intelligence assets.
• Delivery of high-impact business use cases powered by C360 and V360 data.

Ideal Candidate

A hands-on data professional with experience in data warehousing, data enrichment, data procurement, and stakeholder consulting, capable of building and scaling best-in-class Customer 360 and Vehicle 360 platforms while driving measurable business impact.

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