Majesco Migration - Data Architect

Goal:

Define and govern scalable enterprise data architecture that integrates Majesco platforms and enables reliable operations, analytics, and regulatory compliance.

THE MOST RELEVANT SKILL

Enterprise insurance data architecture with Majesco — ability to design, govern, and integrate Majesco Policy/Billing/Claims data models across operational and analytical platforms with high data quality.

SCOPE

• Define and maintain enterprise conceptual, logical, and physical data models for operational systems, data lakes, and warehouses.
• Architect and govern data integration between Majesco Policy, Billing, Claims, Digital1st, and internal/external systems.
• Design ETL/ELT pipelines supporting operational reporting, analytics, and regulatory use cases.
• Establish data governance, metadata, lineage, and data quality controls across platforms.
• Provide technical leadership and architecture reviews for cross-functional delivery teams.
• Support Majesco migrations, upgrades, extractions, and reporting pipelines.

MUST-HAVES (NON-NEGOTIABLE)

• Insurance domain data architecture (P&C preferred) — hands-on modeling of policy, billing, claims, parties, coverages, and transactions.
• Majesco platform data expertise — working knowledge of Majesco Policy/Billing/Claims/Digital1st data models, APIs, and integration patterns.
• Enterprise data modeling — creation and maintenance of conceptual, logical, and physical models using standard tools.
• Relational databases & SQL — advanced querying and schema design on SQL Server, Oracle, or PostgreSQL.
• Data integration architecture — design and oversight of ETL/ELT pipelines for structured/unstructured data.
• Cloud data platforms — implementation using Azure, AWS, or Google Cloud Platform data services (at least one).
• Data governance & quality — definition of standards, MDM concepts, validation rules, lineage, and remediation processes.
• Security & compliance awareness — data protection and regulatory compliance embedded in architecture decisions.
• Technical leadership — translate business requirements into scalable data designs; review and enforce standards.
• Experience level — 8+ years in data architecture, data modeling, or enterprise architecture.

GOOD-TO-HAVES (NEGOTIABLE)

• Azure data stack — Data Factory, Databricks, ADLS, Synapse for large-scale pipelines.
• ACORD standards — mapping and alignment to industry reference models.
• Modern analytics — pipelines enabling advanced analytics and reporting.
• Modernization programs — Majesco transformations or cloud migrations.