HIRING | DATA ARCHITECT – INSURANCE / BFSI

Location: Pan India – Pune, Kolkata, Chennai, Hyderabad, Warangal, Coimbatore, Noida & Bangalore

Experience: 12+ Years

Budget: ₹22.5–24.5 LPA

Shift: 11:30 AM – 9:00 PM

Position: Data Architect

ROLE OVERVIEW

We are looking for an experienced Data Architect with strong Insurance/BFSI domain expertise to lead enterprise-scale data architecture, modernization, and transformation initiatives.

KEY RESPONSIBILITIES

Design and implement enterprise-scale Data Lakes, Data Warehouses & Lakehouse platforms
Define scalable, high-performance and future-ready data architectures
Lead end-to-end program delivery covering scope, schedule, cost and quality
Drive Agile/SAFe planning, governance and execution
Lead implementation, release management and Dev/UAT/Prod environment strategy
Drive performance optimization, DevOps practices and engineering excellence
Enable AI/ML and advanced analytics through robust data platforms
Define enterprise data strategy, governance and compliance frameworks
Lead multi-cloud transformation and modernization initiatives

REQUIRED SKILLS

12+ years of experience in Data Architecture / Enterprise Architecture
Strong Insurance / BFSI domain experience
Hands-on expertise with AWS, Azure & GCP
Strong knowledge of ETL/ELT, Spark, Kafka & distributed data processing
Enterprise data platform and solution architecture expertise
Strong understanding of Data Governance, Security & Compliance
Experience with program/delivery leadership and Agile/SAFe

GOOD TO HAVE

Data catalog, lineage & metadata management tools
GDPR, HIPAA & SOC2 knowledge
Power BI / Tableau
Dataiku, Databricks ML or similar AI/ML platforms

Erforderliche Kompetenzen

Insurance / BFSI domain expertiseEnterprise Data Architecture (Data Lakes, Data Warehouses, Lakehouse)AWSMicrosoft AzureGoogle Cloud Platform (GCP)ETL/ELT and data integrationApache SparkApache Kafka and distributed stream processingData GovernanceData Security & ComplianceProgram and delivery leadership (scope, schedule, cost, quality)Agile / SAFe planning and governanceDevOps and release/environment management for data platformsAI/ML platform enablement (Databricks, Dataiku or similar)Metadata management, data catalog & lineage tools

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